担当区分：最終著者,　責任著者   記述言語：英語   出版者・発行元：Numerical Algorithms  

Graphs have become a commonly used model to study technological, biological, and social systems. Various methods have been proposed to measure graphs’ structural and dynamical properties, providing insights into the fundamental processes and interactions that govern the behavior of these systems. Matrix functions are powerful mathematical tools for assessing vertex centrality, communicability, and diffusion processes. Let M be the adjacency matrix of a weighted undirected graph. Then, the trace of matrix functions, tr(f(M)), provides insights into global network structural and dynamical properties. Although tr(f(M)) can be computed using the diagonalization method for graphs with a few thousand vertices, this approach is impractical for large-scale networks due to its computational complexity. Here, we present a message-passing method to approximate tr(f(M)) for graphs with short cycles that runs in linear time up to logarithmic terms. We compare our proposal with the state-of-the-art approach through simulations and real-world network applications, achieving comparable accuracy in less time.

DOI： 10.1007/s11075-025-02012-0

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担当区分：最終著者,　責任著者   記述言語：英語   出版者・発行元：Studies in Computational Intelligence  

Networks model interactions in complex systems, but traditional features, such as edge counts or centrality, fail to capture their underlying generative processes. While random graph models offer a statistical framework, non-parametric approaches are often needed since the true generative mechanism is unknown. Previous spectral methods, which utilize the eigenvalues of undirected graphs, have enabled tasks such as network comparison and causality detection. However, these methods are limited to undirected graphs, ignoring the directional relationships—such as information flow or regulation—present in many real-world systems. To address this, we extend the spectral analysis to directed graphs by using the full spectrum (both real and imaginary parts) of their asymmetric adjacency matrices. Unlike symmetrizing approaches, our method preserves directional information, enabling more accurate statistical inference in directed networks across various fields, including social science, biology, and communications.

DOI： 10.1007/978-3-032-16645-6_4

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記述言語：英語   出版者・発行元：Aging  

Although transcriptomic changes are known to occur with age, the extent to which these are conserved across tissues is unclear. Previous studies have identified little conservation in age-modulated genes in different tissues. Here, we sought to identify common transcriptional changes with age in humans (aged 20 to 70) across tissues using differential network analysis, assuming that differential expression analysis alone cannot detect all changes in the transcriptional landscape that occur in tissues with age. Our results demonstrate that differential connectivity analysis reveals significant transcriptional alterations that are not detected by differential expression analysis. Combining the two analyses, we identified gene sets modulated by age across all tissues that are highly enriched in terms related to “RNA splicing” and “RNA processing”. The identified genes are also highly interconnected in protein-protein interaction networks. Co-expression module analyses demonstrated that other genes that show tissue-specific variations with age are enriched in pathways that combat the accumulation of aberrant RNAs and proteins, likely caused by defective splicing. Additionally, with convergent connectivity patterns, most tissues significantly reorganized their gene connectivity with age. Our results identified genes and processes whose age-associated transcriptional changes are conserved across tissues, demonstrating a central role for RNA splicing and processing genes and highlighting the importance of differential network analysis for understanding the ageing transcriptome.

DOI： 10.18632/aging.206347

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PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Gut Microbes  

Exclusive breastfeeding (EBF) plays a crucial role in infant gut microbiome assembly and development. However, few studies have investigated the effects of EBF in restoring a perturbed microbiome. In this study, we applied whole metagenomic sequencing to assess the gut microbiome assembly in 525 Brazilian infants from 3 to 9 months of age of the Germina Cohort, demonstrating the early determinants of microbial taxonomy and function modulation. Our analysis shows that EBF alters the relative abundance of genes related to the microbiome taxonomy and function, with effects varying by delivery mode. EBF alters the pattern of carbohydrates, lipid metabolism, and cell structure pathways depending on the delivery mode. The microbiome age is closer to chronological infant age in EBF than in non-EBF infants, meaning a lower microbiome maturation index (MMI). Using a complementary machine learning approach, we show that Escherichia coli, Ruminococcus gnavus, and Clostridium neonatale, as well as vitamin K and o-antigen pathways contribute strongly to EBF prediction. Moreover, EBF influences the microbiome maturation in early life, toward a microbiome age more similar to the chronological infant’s age.

DOI： 10.1080/19490976.2025.2493900

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記述言語：英語   出版者・発行元：Neuroinformatics  

Modelling real-world networks allows investigating the structure and the dynamics of such networks, which led to significant developments in various scientific fields. One of the most used models in these investigations is the Watts-Strogatz, with a structure composed of high clustering and short path lengths known as small-world networks. This model proposes an interesting gradient between regular and random networks, but its generating process, which relies on a single rewiring probability parameter, is hard to access and to manipulate. In order to study the mechanics of the Watts-Strogatz model, the present work proposes a new method based on deep neural networks that could estimate its probability p. To illustrate its applicability, neuroimaging and phenotypic resting-state fMRI data were used from patients with ADHD and typical development children, obtained from the ADHD-200 database. The neural network efficiently estimated the probability parameter, resulting in small-world graphs for functional brain connectivity with a mean ± s.e.m. p distribution of 0.804 ± 0.003. Despite no difference was found considering the gender or diagnosis of participants, the generalized linear model revealed age as a significant predictor of p (mean ± s.e.m.: 4.410 ± 0.877; p < 0.001), indicating a great effect of neurodevelopment on the brain network’s structure. The proposed approach is promising in estimating the probability of the Watts-Strogatz model, and its application has the potential to improve investigations of network connectivity with a relatively efficient and simple framework.

DOI： 10.1007/s12021-025-09756-z

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Development and Psychopathology  

This paper reports the methods and preliminary findings of Germina, an ongoing cohort study to identify biomarkers and trajectories of executive functions and language development in the first 3 years of life. 557 mother-infant dyads (mean age of mothers 33.7 years, 65.2% white, 48.7% male infants) have undergone baseline and are currently collecting data for other timepoints. A linear regression was used to predict baseline Bayley-III using scores derived from data-driven sparse partial least squares utilizing a multiple holdout framework of 15 domains. Significant associations were found between socioeconomic/demographic characteristics (B = 0.29), epigenetics (B = 0.11), EEG theta (B = 0.14) and beta activity (B = 0.11), and microbiome functional pathways (B = 0.08) domains, and infant development measured by the Bayley-III at T1, suggesting potential interventions to prevent impairments.

DOI： 10.1017/S0954579425000069

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PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Art of Discrete and Applied Mathematics  

A cycle in a graph G is said to be primitive from its vertex x if at least one of its edges does not belong to any shorter cycle that passes through x. This type of cycle and an associated notion of extended neighborhoods play a key role in message-passing algorithms that compute spectral properties of graphs with short loops. Here, we investigate such primitive cycles and graphs without long primitive cycles in a more traditional graph-theoretic framework. We show that a cycle is primitive from all its vertices if and only if it is isometric. We call a cycle fully redundant if it is not primitive from any of its vertices and show that fully redundant cycles, in particular, are not edge short, i.e., they cannot be represented as the edge-disjoint union of a single edge and two shortest paths in G. The families R<inf>k</inf> and L<inf>k</inf> of graphs with all cycles of length at least k + 1 being fully redundant and not edge-short, respectively, coincide for k = 3 and k = 4. In these graphs, all cycles of length at least k + 1 are pantochordal, i.e., each of their vertices is incident with a chord. None of these results generalizes to k ≥ 5. Moreover, R<inf>3</inf> = L<inf>3</inf> turn out to be the block graphs, and R<inf>4</inf> = L<inf>4</inf> are the graphs with complete multi-partite blocks. The cographs, finally, are shown to form a proper subset of R<inf>5</inf>

DOI： 10.26493/2590-9770.1754.cd0

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Computational and Structural Biotechnology Journal  

We introduce Pantheon-DNA, an end-to-end processing pipeline for DNA data storage that effectively addresses scalability challenges while efficiently managing large datasets, maintaining ≥99.996% retrievability at 10× coverage under both LER and HER in our tests. To prevent repetitive patterns in DNA sequences, which potentially cause chimeras at the molecular level and also hinder clustering algorithms, we propose a data arrangement scheme and a randomization procedure during encoding. We use block data architecture to enhance parallel processing and retrieval. The proposed sequencing data preprocessing pipeline utilizes prior knowledge of the data structure encoded in the DNA sequences to simplify conventional clustering routines and reduce computational complexity. The system's robustness and reliability are validated through an actual synthesis and sequencing experiment, which encodes and decodes 1.59 MB of data containing multiple files. Future enhancements will focus on refining error correction capabilities, particularly for indel recovery, as well as optimizing preprocessing efficiency and sensitivity.

DOI： 10.1016/j.csbj.2025.09.002

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Journal of Complex Networks  

The spectral density of a graph is a key concept for quantitatively characterizing empirical networks. It has many applications, including community detection, graph signal processing, spectral embedding, network evolution, brain network analysis, and random graph modeling. The graph's spectral density is also crucial in developing statistical methods for graphs, such as model selection and comparative testing. Despite its broad applicability, a complete understanding of the relationship between a graph's spectral density and structure remains elusive. To advance our understanding of the relationship between graph spectra and their structure, we introduce a vertex-wise decomposition of the graph's spectral density, allowing us to determine each vertex's contribution to specific eigenvalues. We show that the decomposition of distinct isospectral graphs (graphs with identical spectra) can be distinguished by the vertex-wise graph spectra, showing that the proposed new quantities are finer invariants between isomorphic graphs. Finally, we apply these insights to analyze chemical molecules and identify genes associated with normal versus tumoral breast gene interaction networks.

DOI： 10.1093/comnet/cnaf013

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Journal of Complex Networks  

Graphs have long been used to model complex systems, but real-world networks often exhibit fluctuations that challenge traditional graph-based methods. Random graph models and spectral techniques have been employed for statistical analysis. However, even these approaches are limited to dyadic relationships, whereas real-world systems often involve more complex interactions. Hypergraphs, which generalize graphs by allowing edges to connect multiple nodes, offer a more accurate representation of such complexity. Therefore, we propose a framework to statistically analyze real-world systems based on the hypergraph's adjacency matrix spectrum. First, we introduce the Kullback-Leibler divergence to compare the spectra of two hypergraphs. We then develop statistical methods for hypergraph analysis, including a parameter estimator, a model selection approach, and a method to test whether two or more hypergraphs were generated by the same process (i.e. the same model and parameter set). Simulation experiments demonstrate the efficacy of our methods. Finally, we apply our approach to real-world hypergraphs as an illustrative example.

DOI： 10.1093/comnet/cnaf019

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Autism Research  

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that combines genetic and environmental factors. The human microbiota is colonized by permanent or transitory microorganisms, depending on the host and the external factors controlling their permanence. The composition of the gut microbiota (GM) in ASD individuals is notably different from that in controls, which may contribute to the clinical conditions observed in these individuals. This study aimed to indirectly investigate the influence of GM on the gut-brain axis in individuals with ASD and controls by analyzing environmental factors that contribute to the microbiota composition. Two questionnaires were designed to collect data, one for the ASD Group (ASDG) and the other one for the Control Group (CG). The raw data from both questionnaires were collected from 2772 respondents. After triage, answers from 1687 ASD individuals, along with 466 respondents from the CG, were analyzed, resulting in a total of 2237 respondents. Our results showed that gastrointestinal problems (GP) escalate as individuals age and become more prominent in ASD individuals. In contrast, feeding problems (FP) did not appear to escalate in either group as individuals aged, even though the FP decreased in the CG. ANOVA revealed significant differences in breastfeeding status compared to GPs among preterm control individuals born via cesarean section (p-value = 0.027). The mean values of GP for breastfed and nonbreastfed individuals, for ASDG (0.257; 0.268) and CG (0.105; 0.248), highlighted the differences in breastfeeding effects on GP for the study groups. The use of antibiotics during pregnancy seemed to be significant for GPs in the ASDG only for breastfed individuals (p-value <0.001), but not in the CG group. In conclusion, variables such as mode of delivery, FPs, type of birth, and length of breastfeeding do not seem to be determining factors for GP in the ASDG but are relevant for the CG. However, for ASDG individuals whose mothers took antibiotics during pregnancy, breastfeeding may act as a protective factor, as maternal antibiotic administration during pregnancy seems to aggravate GP-values across the ages of the participants. Considering GP as a proxy for GM and recognizing the importance of GM composition for central nervous system (CNS) function, it appears that in individuals with ASD, GM seems to be more dependent on other factors, which might be linked to the genetic background of each one. These findings suggest that future studies of the gut-brain axis in individuals with ASD might consider the individual's genetic background, environmental factors, and GM.

DOI： 10.1002/aur.3263

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Frontiers in Public Health  

Infants growing up in low- and middle-income countries are at increased risk of suffering adverse childhood experiences, including exposure to environmental pollution and lack of cognitive stimulation. In this study, we aimed to examine the levels of metals in the human milk of women living in São Paulo City, Brazil, and determine the effects on infants’ neurodevelopment. For such, a total of 185 human milk samples were analyzed for arsenic (As), lead (Pb), mercury (Hg), and cadmium (Cd) using inductively coupled plasma mass spectrometry (ICP-MS). We applied the Bayley scales of infant and toddler development Third Edition (Bayley-III) to assess developmental milestones. In our analysis, we found a mean (standard deviation) concentration of As in human milk equal to 2.76 (4.09) μg L−1, followed by Pb 2.09 (5.36) and Hg 1.96 (6.68). Cd was not detected. We observed that infants exposed to Pb presented language trajectories lower than non-exposed infants (β = −0.413; 95% CI -0.653, −0.173) after adjustment for infant age, maternal education, socioeconomic status, infant sex, and sample weights. Our results report As, Pb, and Hg contamination in human milk, and that infant exposure to Pb decreased infants’ language development. These results evidence maternal-child environmental exposure and its detrimental impact on infants’ health.

DOI： 10.3389/fpubh.2024.1450570

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記述言語：英語   出版者・発行元：eLife Sciences Publications, Ltd  

Abstract

Active, directed locomotion on the ground is present in many phylogenetically distant species. Bilateral symmetry and modularity of the body are common traits often associated with improved directed locomotion. Nevertheless, both features result from natural selection, which is contingent (history-dependent) and multifactorial (several factors interact simultaneously). Based solely on the unique natural history on Earth, it is difficult to conclude that bilateral symmetry and modularity of the body are required traits for an improved locomotion ability as they can result from chance or be related to other body functions. As a way to avoid these caveats, we propose using physics-based simulations of 3D voxel-based soft robots evolved under different evolutionary scenarios to test the necessity of both traits for sustained and effective displacement on the ground. We found that an intermediate number of body modules (appendages) and high body symmetry are evolutionarily selected regardless of gravitational environments, robot sizes, and genotype encoding. Therefore, we conclude that both traits are strong candidates for universal principles related to improved directed locomotion.

DOI： 10.7554/elife.87180.2

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Wiley  

ABSTRACT

Background

Cancer cachexia, systemic inflammation and muscle wasting are associated with poor survival in non–small cell lung cancer (NSCLC) patients (pts). We hypothesized whether neutrophil‐to‐lymphocyte ratio (NLR) and intramuscular adipose tissue/skeletal muscle index (IMAT/SMI) would predict prognosis in metastatic NSCLC (mNSCLC). In addition, we verified the role of a cancer cachexia questionnaire (EORTC‐QLQ‐CAX24) in the survival prediction.

Methods

We analysed a prospective cohort of 128 treatment‐naive mNSCLC pts (April 2017 to May 2020). We evaluated QoL using the EORTC‐QLQ‐C30 and EORTC‐QLQ‐CAX24 scales. We used the baseline NLR as a surrogate of systemic inflammation. We did evaluate IMAT/SMI using baseline plain computed tomography imaging. Cox multivariate regression, including age, sex, ECOG‐PS and histology as covariates, was performed.

Results

Elevated NLR (hazard ratio [HR] 1.26, 95% confidence interval [CI]: 1.01–1.59, p = 0.038), IMAT/SMI ratio (HR 1.37, 95% CI: 1.03–1.84, p = 0.032) and high CAX24 scores for food aversion (HR 1.52, 95% CI: 1.13–2.03, p = 0.006) were associated with worse prognosis in mNSCLC. Indeed, higher ECOG‐PS (Spearman rho = 0.208, p = 0.027), CAX24 scores for food aversion (Spearman rho = 0.197, p = 0.036), loss of control (Spearman rho = 0.212, p = 0.024) and eating and weight loss worry domains (Spearman rho = 0.219, p = 0.020) were associated with elevated NLR levels.

Conclusions

Elevated NLR, IMAT/SMI ratio and CAX24 score for food aversion are independently associated with worse survival in mNSCLC. These data underscored the importance of cachexia features as negative prognostic factors in mNSCLC and revealed the EORTC‐QLQ‐CAX24 questionnaire as a new tool for helping clinical decision‐making.

Trial Registration: ClinicalTrials.gov identifier: NCT03960034 and NCT04306094

DOI： 10.1002/rco2.106

記述言語：英語   掲載種別：研究論文（学術雑誌）  

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：American Journal of Psychiatry  

OBJECTIVE: Previous population-based studies have identified associations between childhood neurodevelopmental traits and depression in childhood, adolescence, and young adulthood. However, neurodevelopmental traits are highly correlated with each other, which could confound associations when traits are examined in isolation. The authors sought to identify unique associations between multiple neurodevelopmental traits in childhood and depressive symptoms across development, while taking into account co-occurring difficulties, in multivariate analyses. METHODS: Data from two U.K. population-based cohorts, the Twins Early Development Study (TEDS) (N=4,407 independent twins) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (N=10,351), were independently analyzed. Bayesian Gaussian graphical models were estimated to investigate pairwise conditional associations between neurodevelopmental traits (autism and ADHD symptoms and general cognitive, learning, and communication abilities), socioenvironmental stressors (academic performance and peer relations), and emotional dysregulation in childhood (ages 7-11) and depressive symptoms across development (ages 12, 16, and 21). RESULTS: In both cohorts, bivariate correlations indicated several associations between neurodevelopmental traits and depressive symptoms across development. However, based on replicated findings across cohorts, these pairs of variables were mostly conditionally independent, and none were conditionally associated, after accounting for socioenvironmental stressors and emotional dysregulation. In turn, socioenvironmental stressors and emotional dysregulation were conditionally associated with both neurodevelopmental traits and depressive symptoms. Based on replicated findings across cohorts, neurodevelopmental traits in childhood could be associated only indirectly with depressive symptoms across development. CONCLUSIONS: This study indicates that associations between childhood neurodevelopmental traits and depressive symptoms across development could be explained by socioenvironmental stressors and emotional dysregulation. The present findings could inform future research aimed at the prevention of depression in youths with neurodevelopmental disorders.

DOI： 10.1176/appi.ajp.20220868

DOI： 10.1176/appi.ajp.20220868

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PubMed

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）  

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Journal of Complex Networks  

Graphs have become crucial for representing and examining biological, social and technological interactions. In this context, the graph spectrum is an exciting feature to be studied because it encodes the structural and dynamic characteristics of the graph. Hence, it becomes essential to efficiently compute the graph's spectral distribution (eigenvalue's density function). Recently, some authors proposed degree-based methods to obtain the spectral density of locally tree-like networks in linear time. The bottleneck of their approach is that they assumed that the graph's assortativity is zero. However, most real-world networks, such as social and biological networks, present assortativity. Consequently, their spectral density approximations may be inaccurate. Here, we propose a method that considers assortativity. Our algorithm's time and space complexities are O(d2), where d is the largest degree of the graph. Finally, we show our method's efficacy in simulated and empirical networks.

DOI： 10.1093/comnet/cnad005

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Pnas Nexus  

Uncontrolled vasodilation is known to account for hypotension in the advanced stages of sepsis and other systemic inflammatory conditions, but the mechanisms of hypotension in earlier stages of such conditions are not clear. By monitoring hemodynamics with the highest temporal resolution in unanesthetized rats, in combination with ex-vivo assessment of vascular function, we found that early development of hypotension following injection of bacterial lipopolysaccharide is brought about by a fall in vascular resistance when arterioles are still fully responsive to vasoactive agents. This approach further uncovered that the early development of hypotension stabilized blood flow. We thus hypothesized that prioritization of the local mechanisms of blood flow regulation (tissue autoregulation) over the brain-driven mechanisms of pressure regulation (baroreflex) underscored the early development of hypotension in this model. Consistent with this hypothesis, an assessment of squared coherence and partial-directed coherence revealed that, at the onset of hypotension, the flow–pressure relationship was strengthened at frequencies (<0.2 Hz) known to be associated with autoregulation. The autoregulatory escape to phenylephrine-induced vasoconstriction, another proxy of autoregulation, was also strengthened in this phase. The competitive demand that drives prioritization of flow over pressure regulation could be edema-associated hypovolemia, as this became detectable at the onset of hypotension. Accordingly, blood transfusion aimed at preventing hypovolemia brought the autoregulation proxies back to normal and prevented the fall in vascular resistance. This novel hypothesis opens a new avenue of investigation into the mechanisms that can drive hypotension in systemic inflammation.

DOI： 10.1093/pnasnexus/pgad014

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PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）  

BACKGROUND: Patients with advanced non-small cell lung cancer (NSCLC) are a heterogeneous population with short lifespan. We aimed to develop methods to better differentiate patients whose survival was >90 days. METHODS: We evaluated 83 characteristics of 106 treatment-naïve, stage IV NSCLC patients with Eastern Cooperative Oncology Group Performance Status (ECOG-PS) >1. Automated machine learning was used to select a model and optimize hyperparameters. 100-fold bootstrapping was performed for dimensionality reduction for a second ("lite") model. Performance was measured by C-statistic and accuracy metrics in an out-of-sample validation cohort. The "lite" model was validated on a second independent, prospective cohort (N = 42). Network analysis (NA) was performed to evaluate the differences in centrality and connectivity of features. RESULTS: The selected method was ExtraTrees Classifier, with C-statistic of 0.82 (p < 0.01) and accuracy of 0.81 (p = 0.01). The "lite" model had 16 variables and obtained C-statistic of 0.84 (p < 0.01) and accuracy of 0.75 (p = 0.039) in the first cohort, and C-statistic of 0.706 (p < 0.01) and accuracy of 0.714 (p < 0.01) in the second cohort. The networks of patients with lower survival were more interconnected. Features related to cachexia, inflammation, and quality of life had statistically different prestige scores in NA. CONCLUSIONS: Machine learning can assist in the prognostic evaluation of advanced NSCLC. The model generated with a reduced number of features showed high accessibility and reasonable metrics. Features related to quality of life, cachexia, and performance status had increased correlation and importance scores, suggesting that they play a role at later disease stages, in line with the biological rationale already described.

DOI： 10.1002/cam4.5254

PubMed

記述言語：英語   掲載種別：研究論文（学術雑誌）  

記述言語：英語   掲載種別：研究論文（学術雑誌）  

担当区分：責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：World Scientific Pub Co Pte Ltd  

<jats:p> Usually, the clustering process is the first step in several data analyses. Clustering allows identify patterns we did not note before and helps raise new hypotheses. However, one challenge when analyzing empirical data is the presence of covariates, which may mask the obtained clustering structure. For example, suppose we are interested in clustering a set of individuals into controls and cancer patients. A clustering algorithm could group subjects into young and elderly in this case. It may happen because the age at diagnosis is associated with cancer. Thus, we developed CEM-Co, a model-based clustering algorithm that removes/minimizes undesirable covariates’ effects during the clustering process. We applied CEM-Co on a gene expression dataset composed of 129 stage I non-small cell lung cancer patients. As a result, we identified a subgroup with a poorer prognosis, while standard clustering algorithms failed. </jats:p>

DOI： 10.1142/S0219720023500191

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CiNii Research

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Frontiers in Neuroscience  

Introduction: Clustering is usually the first exploratory analysis step in empirical data. When the data set comprises graphs, the most common approaches focus on clustering its vertices. In this work, we are interested in grouping networks with similar connectivity structures together instead of grouping vertices of the graph. We could apply this approach to functional brain networks (FBNs) for identifying subgroups of people presenting similar functional connectivity, such as studying a mental disorder. The main problem is that real-world networks present natural fluctuations, which we should consider. Methods: In this context, spectral density is an exciting feature because graphs generated by different models present distinct spectral densities, thus presenting different connectivity structures. We introduce two clustering methods: k-means for graphs of the same size and gCEM, a model-based approach for graphs of different sizes. We evaluated their performance in toy models. Finally, we applied them to FBNs of monkeys under anesthesia and a dataset of chemical compounds. Results: We show that our methods work well in both toy models and real-world data. They present good results for clustering graphs presenting different connectivity structures even when they present the same number of edges, vertices, and degree of centrality. Discussion: We recommend using k-means-based clustering for graphs when graphs present the same number of vertices and the gCEM method when graphs present a different number of vertices.

DOI： 10.3389/fnins.2023.926321

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Clinical Epigenetics  

The epigenetic changes associated with melanoma progression to advanced and metastatic stages are still poorly understood. To shed light on the CpG methylation dynamics during melanoma development, we analyzed the methylome profiles of a four-stage cell line model of melanoma progression: non-tumorigenic melanocytes (melan-a), premalignant melanocytes (4C), non-metastatic melanoma cells (4C11−), and metastatic melanoma cells (4C11+). We identified 540 hypo- and 37 hypermethylated gene promoters that together characterized a malignancy signature, and 646 hypo- and 520 hypermethylated promoters that distinguished a metastasis signature. Differentially methylated genes from these signatures were correlated with overall survival using TCGA-SKCM methylation data. Moreover, multivariate Cox analyses with LASSO regularization identified panels of 33 and 31 CpGs, respectively, from the malignancy and metastasis signatures that predicted poor survival. We found a concordant relationship between DNA methylation and transcriptional levels for genes from the malignancy (Pyroxd2 and Ptgfrn) and metastasis (Arnt2, Igfbp4 and Ptprf) signatures, which were both also correlated with melanoma prognosis. Altogether, this study reveals novel CpGs methylation markers associated with malignancy and metastasis that collectively could improve the survival prediction of melanoma patients.

DOI： 10.1186/s13148-022-01291-x

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掲載種別：研究論文（学術雑誌）   出版者・発行元：Brazilian Journal of Physics  

In this paper, we introduce a billiard whose boundary varies from a circular to a polygonal billiard. To describe the billiard boundary, we use a parametric equation, which needs to be solved numerically. We provide a detailed explanation about how to obtain the radius of the billiard boundary R for each angular position θ, where we used a tangent method to speed up the numerical simulations. We consider another tangent method to find the billiard boundary’s intercept and the particle’s trajectory. Furthermore, we show some trajectories’ examples and describe what happens with the phase space and Lyapunov exponents when changing the deformation. We present results for different values of the control parameter related to the number of edges of our polygon and the billiard with a triangular-like boundary.

DOI： 10.1007/s13538-022-01075-x

Scopus

その他リンク： https://link.springer.com/article/10.1007/s13538-022-01075-x/fulltext.html

掲載種別：研究論文（学術雑誌）   出版者・発行元：Chaos Solitons and Fractals  

In this paper, we study some dynamic properties for oval-like billiards. These billiards have two control parameters, named ϵ, which controls the deformation of the boundary, and p, which changes the number of inflection points. The particle's position (X,Y) uses Cartesian coordinates, and the angle μ gives us the particle's direction. Here we consider a Poincare section, where we calculate the position X (in the horizontal axis) and angle μ every time a particle crosses Y=0 (in the vertical axis). We compute the phase space and the conservative generalized bifurcation diagrams (CGBD). These diagrams are obtained when changing the initial position X and the control parameter ϵ. We plot the respective maximum Lyapunov exponent for each combination of the control parameter and initial condition, which uses a customized color palette. These diagrams show how complex billiards dynamics are, where one can find the direct and inverse parabolic bifurcations. Moreover, one can highlight periodic, quasi-periodic, and chaotic regions. We found a fractal behavior (self-similar structure), where we verified the existence of period-adding structures logical sequences (periodic orbits) in the CGBD. These sequences accumulate in different regions depending on the control parameters, following the main body's period and accumulating in different regions. When we set the control parameter p to 1, we observe that chaos dominates for a high enough value of the control parameter ϵ (which controls our billiard's deformation). We also studied some orbits embedded in stochastic layers that appear near saddle points, which obey another period-adding logical sequence. These stochastic layers play a crucial role in the dynamics of billiard systems because that chaos grows in such regions, near saddle points, after increasing the control parameter's value.

DOI： 10.1016/j.chaos.2021.111707

Scopus

担当区分：最終著者,　責任著者   掲載種別：研究論文（学術雑誌）  

DOI： 10.1093/comnet/cnac022

担当区分：最終著者,　責任著者   掲載種別：研究論文（学術雑誌）   出版者・発行元：Journal of Complex Networks  

Estimating the number of eigenvalues μ[a,b] of a network's adjacency matrix in a given interval [a,b] is essential in several fields. The straightforward approach consists of calculating all the eigenvalues in O(n3) (where n is the number of nodes in the network) and then counting the ones that belong to the interval [a,b]. Another approach is to use Sylvester's law of inertia, which also requires O(n3). Although both methods provide the exact number of eigenvalues in [a,b], their application for large networks is computationally infeasible. Sometimes, an approximation of μ[a,b] is enough. In this case, Chebyshev's method approximates μ[a,b] in O(|E|) (where |E| is the number of edges). This study presents two alternatives to compute μ[a,b] for locally tree-like networks: Edge- A nd degree-based algorithms. The former presented a better accuracy than Chebyshev's method. It runs in O(d|E|), where d is the number of iterations. The latter presented slightly lower accuracy but ran linearly (O(n)).

DOI： 10.1093/comnet/cnac040

Scopus

記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Frontiers in Computational Neuroscience  

Hyperscanning is a promising tool for investigating the neurobiological underpinning of social interactions and affective bonds. Recently, graph theory measures, such as modularity, have been proposed for estimating the global synchronization between brains. This paper proposes the bootstrap modularity test as a way of determining whether a pair of brains is coactivated. This test is illustrated as a screening tool in an application to fNIRS data collected from the prefrontal cortex and temporoparietal junction of five dyads composed of a teacher and a preschooler while performing an interaction task. In this application, graph hub centrality measures identify that the dyad's synchronization is critically explained by the relation between teacher's language and number processing and the child's phonological processing. The analysis of these metrics may provide further insights into the neurobiological underpinnings of interaction, such as in educational contexts.

DOI： 10.3389/fncom.2022.975743

Scopus

PubMed