A Principled Framework to Assess the Information-Theoretic Fitness of Brain Functional Sub-Circuits.

In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects' functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold.

Caudal and Thalamic Segregation in White Matter Brain Network Communities in Alzheimer's Disease Population.

Neuroimaging studies have demonstrated that Alzheimer's disease (AD) is closely related to changes in neuroanatomy in the form of damage to both grey matter and white matter. However, the exact nature of AD's relationship with white matter anatomical deterioration is not fully understood at a systemic level. To investigate this knowledge gap, we constructed structural brain networks from ADNI-GO/2 diffusion tensor imaging (DTI) images with brain regions of interest (ROIs) as nodes and white matter connections as edges weighted by fiber density.

Supervised brain node and network construction under voxel-level functional imaging.

Recent advancements in understanding the brain's functional organization related to behavior have been pivotal, particularly in the development of predictive models based on brain connectivity. A major analytical strategy in this domain involves a two-step process by first constructing a connectivity matrix from predefined brain regions, and then linking these connections to behaviors or clinical outcomes. Although some advances considered subject-specific functionally homogeneous nodes without relying on predefined regions of interest (ROIs), all these approaches with unsupervised node partitions predict outcomes inefficiently with independently established connectivity.

Heritability and genetic contribution analysis of structural-functional coupling in human brain.

The flow of functional connectivity (FC) is thought to be supported by white matter structural connectivity (SC). While research on the correlations between SC and FC (SC-FC coupling) has progressed, the genetic implications of SC-FC coupling have not been thoroughly examined. Traditionally, SC-FC coupling investigations utilize predefined atlases.

Covariance-on-covariance regression.

A covariance-on-covariance regression model is introduced in this manuscript. It is assumed that there exists (at least) a pair of linear projections on outcome covariance matrices and predictor covariance matrices such that a log-linear model links the variances in the projection spaces, as well as additional covariates of interest. An ordinary least square type of estimator is proposed to simultaneously identify the projections and estimate model coefficients.

Comparative analysis of the correlation between paraspinal muscles fat infiltration and vertebral bone quality in patients with lumbar degenerative diseases.

Purpose: This study aimed to comprehensively evaluate the association between paraspinal muscle fat infiltration (FI) and three MRI-based vertebral bone quality indicators-Vertebral Bone Quality (VBQ), Modified VBQ (MVBQ), and Endplate Bone Quality (EBQ)-in patients with lumbar degenerative diseases (LDD), and to compare their diagnostic and prognostic implications.

Methods: A retrospective analysis included 261 patients undergoing transforaminal lumbar interbody fusion (TLIF) for LDD. Paraspinal muscle parameters-total cross-sectional area (TCSA), functional CSA (FCSA), relative FCSA (rFCSA), and fat infiltration rate (FIR)-were obtained from preoperative MRI.

Cost Efficiency of fMRI Studies Using Resting-State Vs. Task-Based Functional Connectivity.

We investigate whether and how we can improve the cost efficiency of neuroimaging studies with well-tailored fMRI tasks. The comparative study is conducted using a novel network science-driven Bayesian connectome-based predictive method, which incorporates network theories in model building and substantially improves precision and robustness in imaging biomarker detection. The robustness of the method lays the foundation for identifying predictive power differentials across fMRI task conditions if such differences exist.

Liquid biopsy for promoter methylation in prostate cancer: a promising non-invasive diagnostic weapon.

Objective: Prostate-specific antigen (PSA) has served as a screening tool for prostate cancer (PCa) for over 30 years, but its low specificity remains a significant limitation. Liquid biopsy based on promoter methylation, an epigenetic modification, holds significant potential to complement PSA testing and enhance the diagnostic accuracy of PCa. Our objective was to assess the diagnostic accuracy of liquid biopsy for promoter methylation in PCa.

scMODAL: a general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links.

Recent advancements in single-cell technologies have enabled comprehensive characterization of cellular states through transcriptomic, epigenomic, and proteomic profiling at single-cell resolution. These technologies have significantly deepened our understanding of cell functions and disease mechanisms from various omics perspectives. As these technologies evolve rapidly and data resources expand, there is a growing need for computational methods that can integrate information from different modalities to facilitate joint analysis of single-cell multi-omics data.

Semiparametric joint modeling for biomarker trajectory before disease onset.

Understanding how biomarkers change in relation to disease pathogenesis is a key area in biomedical research. We propose a semiparametric joint model to analyze the temporal evolution of biomarkers prior to the onset of disease. The model allows for a flexible biomarker trajectory that depends on two time scales: a natural time scale such as age and time to disease onset.

Geriatric nutrition risk index is useful to assess the risk of postoperative urinary retention in elderly patient undergoing lumber interbody fusion.

Objective: To investigate whether the Geriatric Nutrition Risk Index (GNRI) can serve as an independent predictor of postoperative urinary retention (PUR) in elderly patients undergoing transforaminal lumbar interbody fusion (TLIF).

Methods: This retrospective study reviewed elderly patients who underwent TLIF at a single institution between 2016 and 2021. Patients diagnosed with PUR during hospitalization were identified.

Bayesian Longitudinal Network Regression With Application to Brain Connectome Genetics.

The increasing availability of large-scale brain imaging genetics studies enables more comprehensive exploration of the genetic underpinnings of brain functional organizations. However, fundamental analytical challenges arise when considering the complex network topology of brain functional connectivity, influenced by genetic contributions and sample relatedness, particularly in longitudinal studies. In this paper, we propose a novel method named Bayesian Longitudinal Network-Variant Regression (BLNR), which models the association between genetic variants and longitudinal brain functional connectivity.

A genetically informed brain atlas for enhancing brain imaging genomics.

Brain imaging genomics has manifested considerable potential in illuminating the genetic determinants of human brain structure and function. This has propelled us to develop the GIANT (Genetically Informed brAiN aTlas) that accounts for genetic and neuroanatomical variations simultaneously. Integrating voxel-wise heritability and spatial proximity, GIANT clusters brain voxels into genetically informed regions, while retaining fundamental anatomical knowledge.

Evaluating surgical interventions for low-grade degenerative lumbar spondylolisthesis: a network meta-analysis of decompression alone, fusion, and dynamic stabilization.

Objective: This study aimed to investigate which of the decompression alone (DA), decompression with fusion (DF), and decompression with dynamic stabilization (DS) produced the most favorable outcome for patients with low-grade degenerative lumbar spondylolisthesis (LDLS).

Material And Method: Pubmed, Embase, Cochrane, and Web of Science were searched for all studies published before October 1, 2023. A review and data analysis of all randomized controlled trials (RCTs) of three interventions was performed by Stata (version 17.

Burden of Atrial Fibrillation and Atrial Flutter From 1990 to 2021 in China: Global Burden of Disease Study 2021 Update.

Background: Atrial fibrillation (AF) and atrial flutter (AFL) represent increasingly significant health burden globally. We aimed to systematically evaluate the status and trends of AF/AFL burden and attributable risk factors in China.

Methods: We assessed the burden of AF/AFL measured as prevalence, incidence, mortality, and disability-adjusted life years (DALYs), by sex and age groups in China based on the Global Burden of Diseases Study (GBD) 2021 project.

Volume-optimal persistence homological scaffolds of hemodynamic networks covary with MEG theta-alpha aperiodic dynamics.

Higher-order properties of functional magnetic resonance imaging (fMRI) induced connectivity have been shown to unravel many exclusive topological and dynamical insights beyond pairwise interactions. Nonetheless, whether these fMRI-induced higher-order properties play a role in disentangling other neuroimaging modalities' insights remains largely unexplored and poorly understood. In this work, by analyzing fMRI data from the Human Connectome Project Young Adult dataset using persistent homology, we discovered that the volume-optimal persistence homological scaffolds of fMRI-based functional connectomes exhibited conservative topological reconfigurations from the resting state to attentional task-positive state.

Antiseizure Medications in Poststroke Seizures: A Systematic Review and Network Meta-Analysis.

Background And Objectives: The most effective antiseizure medications (ASMs) for poststroke seizures (PSSs) remain unclear. We aimed to determine outcomes associated with ASMs in people with PSS.

Methods: We systematically searched electronic databases for studies on patients with PSS on ASMs.

Bayesian thresholded modeling for integrating brain node and network predictors.

Progress in neuroscience has provided unprecedented opportunities to advance our understanding of brain alterations and their correspondence to phenotypic profiles. With data collected from various imaging techniques, studies have integrated different types of information ranging from brain structure, function, or metabolism. More recently, an emerging way to categorize imaging traits is through a metric hierarchy, including localized node-level measurements and interactive network-level metrics.

Bayesian subtyping for multi-state brain functional connectome with application on preadolescent brain cognition.

Converging evidence indicates that the heterogeneity of cognitive profiles may arise through detectable alternations in brain functional connectivity. Despite an unprecedented opportunity to uncover neurobiological subtypes through clustering or subtyping analyses on multi-state functional connectivity, few existing approaches are applicable to accommodate the network topology and unique biological architecture. To address this issue, we propose an innovative Bayesian nonparametric network-variate clustering analysis to uncover subgroups of individuals with homogeneous brain functional network patterns under multiple cognitive states.

Sex-specific topological structure associated with dementia via latent space estimation.

Introduction: We investigate sex-specific topological structures associated with typical Alzheimer's disease (AD) dementia using a novel state-of-the-art latent space estimation technique.

Methods: This study applies a probabilistic approach for latent space estimation that extends current multiplex network modeling approaches and captures the higher-order dependence in functional connectomes by preserving transitivity and modularity structures.

Results: We find sex differences in network topology with females showing more default mode network (DMN)-centered hyperactivity and males showing more limbic system (LS)-centered hyperactivity, while both show DMN-centered hypoactivity.

Bayesian pathway analysis over brain network mediators for survival data.

Technological advancements in noninvasive imaging facilitate the construction of whole brain interconnected networks, known as brain connectivity. Existing approaches to analyze brain connectivity frequently disaggregate the entire network into a vector of unique edges or summary measures, leading to a substantial loss of information. Motivated by the need to explore the effect mechanism among genetic exposure, brain connectivity, and time to disease onset with maximum information extraction, we propose a Bayesian approach to model the effect pathway between each of these components while quantifying the mediating role of brain networks.

Stem Cell Membrane-Camouflaged Biomimetic Nanoparticles Inhibiting Leptin Pathway for Intervertebral Disc Degeneration Therapy.

Leptin, a kind of adipokine, with its receptor in which the long isoform plays a crucial role in signal transduction, has been identified in intervertebral disc (IVD) tissues, especially showing an increased expression in degenerated discs. Initially identified as a metabolic sensor, leptin has recently been found able to regulate inflammation into imbalance, which favors catabolic degradative processes, thus contributing to progressive intervertebral disc degeneration (IDD). Therefore, efficiently inhibiting the leptin pathway may provide a new strategy to treat IDD.

Association of social support with depression and anxiety among the migrant population of Henan, China: Based on a large cross-sectional study.

Amid China's rapid urbanization, the growing migrant population has increasingly drawn attention due to the rising prevalence of mental health concerns. Based on a large cross-sectional study, we explored the relationship between social factors and depression and anxiety among the migrant population and also quantified the correlations of different dimensions of social support and the varying levels of depression and anxiety. Results showed that the prevalence of depression and anxiety are 47.

A Nanoparticle-Coated Cellulose Acetate Membrane for Highly Efficient, Low-Cost Circulating Tumor Cell Detection.

Detecting circulating tumor cells has exhibited great significance in treating cancers since its concentration is an index strongly associated with the development and transfer of the tumor. However, the present commercial method for CTC detection is still expensive, because special antibodies and complicated devices must be used for cell separation and imaging. Hence, it is quite necessary to apply alternative materials and methods to decrease the cost of CTC detection.