Of mice and men: Dendritic architecture differentiates human from mice neuronal networks.

The organizational principles that distinguish the human brain from other species have been a long-standing enigma in neuroscience. Focusing on the uniquely evolved human cortical layers 2 and 3, we computationally reconstruct the cortical architecture for mice and humans. We show that human pyramidal cells form highly complex networks, demonstrated by the increased number and simplex dimension compared to mice.

Dynamics of CLIMP-63 S-acylation control ER morphology.

The complex architecture of the endoplasmic reticulum (ER) comprises distinct dynamic features, many at the nanoscale, that enable the coexistence of the nuclear envelope, regions of dense sheets and a branched tubular network that spans the cytoplasm. A key player in the formation of ER sheets is cytoskeleton-linking membrane protein 63 (CLIMP-63). The mechanisms by which CLIMP-63 coordinates ER structure remain elusive.

Extracellular Vesicle MicroRNA in Malignant Pleural Effusion.

Lung and breast cancer are the two most common causes of malignant pleural effusion (MPE). MPE diagnosis plays a crucial role in determining staging and therapeutic interventions in these cancers. However, our understanding of the pathogenesis and progression of MPE at the molecular level is limited.

A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes.

Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability.

Intact central nervous system cellular quantitation reveals sexual dimorphism.

Establishing with precision the quantity and identity of the cell types of the brain is a prerequisite for a detailed compendium of gene and protein expression in the central nervous system (CNS). Currently, however, strict quantitation of cell numbers has been achieved only for the nervous system of . Here, we describe the development of a synergistic pipeline of molecular genetic, imaging, and computational technologies designed to allow high-throughput, precise quantitation with cellular resolution of reporters of gene expression in intact whole tissues with complex cellular constitutions such as the brain.

Computational synthesis of cortical dendritic morphologies.

Neuronal morphologies provide the foundation for the electrical behavior of neurons, the connectomes they form, and the dynamical properties of the brain. Comprehensive neuron models are essential for defining cell types, discerning their functional roles, and investigating brain-disease-related dendritic alterations. However, a lack of understanding of the principles underlying neuron morphologies has hindered attempts to computationally synthesize morphologies for decades.

Digital Reconstruction of the Neuro-Glia-Vascular Architecture.

Astrocytes connect the vasculature to neurons mediating the supply of nutrients and biochemicals. They are involved in a growing number of physiological and pathophysiological processes that result from biophysical, physiological, and molecular interactions in this neuro-glia-vascular ensemble (NGV). The lack of a detailed cytoarchitecture severely restricts the understanding of how they support brain function.

Topology predicts long-term functional outcome in early psychosis.

Early intervention in psychosis is crucial to improving patient response to treatment and the functional deficits that critically affect their long-term quality of life. Stratification tools are needed to personalize functional deficit prevention strategies at an early stage. In the present study, we applied topological tools to analyze symptoms of early psychosis patients, and detected a clear stratification of the cohort into three groups.

Topological exploration of artificial neuronal network dynamics.

One of the paramount challenges in neuroscience is to understand the dynamics of individual neurons and how they give rise to network dynamics when interconnected. Historically, researchers have resorted to graph theory, statistics, and statistical mechanics to describe the spatiotemporal structure of such network dynamics. Our novel approach employs tools from algebraic topology to characterize the global properties of network structure and dynamics.

The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness.

How can we explain consciousness? This question has become a vibrant topic of neuroscience research in recent decades. A large body of empirical results has been accumulated, and many theories have been proposed. Certain theories suggest that consciousness should be explained in terms of brain functions, such as accessing information in a global workspace, applying higher order to lower order representations, or predictive coding.

Two-Tier Mapper, an unbiased topology-based clustering method for enhanced global gene expression analysis.

Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex datasets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small datasets. To overcome these shortcomings we used topological data analysis, an emerging field of mathematics that discerns additional feature and discovers hidden insights on datasets and has a wide application range.

Objective Morphological Classification of Neocortical Pyramidal Cells.

A consensus on the number of morphologically different types of pyramidal cells (PCs) in the neocortex has not yet been reached, despite over a century of anatomical studies, due to the lack of agreement on the subjective classifications of neuron types, which is based on expert analyses of neuronal morphologies. Even for neurons that are visually distinguishable, there is no common ground to consistently define morphological types. The objective classification of PCs can be achieved with methods from algebraic topology, and the dendritic arborization is sufficient for the reliable identification of distinct types of cortical PCs.

High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites.

The materials genome initiative has led to the creation of a large (over a million) database of different classes of nanoporous materials. As the number of hypothetical materials that can, in principle, be experimentally synthesized is infinite, a bottleneck in the use of these databases for the discovery of novel materials is the lack of efficient computational tools to analyze them. Current approaches use brute-force molecular simulations to generate thermodynamic data needed to predict the performance of these materials in different applications, but this approach is limited to the analysis of tens of thousands of structures due to computational intractability.

A Topological Representation of Branching Neuronal Morphologies.

Many biological systems consist of branching structures that exhibit a wide variety of shapes. Our understanding of their systematic roles is hampered from the start by the lack of a fundamental means of standardizing the description of complex branching patterns, such as those of neuronal trees. To solve this problem, we have invented the Topological Morphology Descriptor (TMD), a method for encoding the spatial structure of any tree as a "barcode", a unique topological signature.

Cliques of Neurons Bound into Cavities Provide a Missing Link between Structure and Function.

The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity.

Quantifying similarity of pore-geometry in nanoporous materials.

In most applications of nanoporous materials the pore structure is as important as the chemical composition as a determinant of performance. For example, one can alter performance in applications like carbon capture or methane storage by orders of magnitude by only modifying the pore structure. For these applications it is therefore important to identify the optimal pore geometry and use this information to find similar materials.

Evaluating the Extent of Clinical Variability Among Treatment Options for Patients With Adult Spinal Deformity.

Study Design: This is a surgical strategy survey.

Objective: The purpose of this study was to evaluate the variability in in surgical strategy planning of adult spinal deformity (ASD) based on patients' clinical and radiographic data.

Background: Literature guiding the management of ASD consists primarily of studies with low levels of evidence.

Sacral Insufficiency Fractures are Common After High-dose Radiation for Sacral Chordomas Treated With or Without Surgery.

Background: Surgery with high-dose radiation and high-dose radiation alone for sacral chordomas have shown promising local control rates. However, we have noted frequent sacral insufficiency fractures and perceived this rate to be higher than previously reported.

Questions/purposes: We wished (1) to characterize the incidence of sacral insufficiency fractures in patients with chordomas of the sacrum who received high-dose radiation, and (2) to determine whether patients treated with surgery plus high-dose radiation or high-dose radiation alone are more likely to experience a sacral fracture, and to compare time to fracture in these groups.

Progesterone and Overlooked Endocrine Pathways in Breast Cancer Pathogenesis.

Worldwide, breast cancer incidence has been increasing for decades. Exposure to reproductive hormones, as occurs with recurrent menstrual cycles, affects breast cancer risk, and can promote disease progression. Exogenous hormones and endocrine disruptors have also been implicated in increasing breast cancer incidence.

How Does the Level of Sacral Resection for Primary Malignant Bone Tumors Affect Physical and Mental Health, Pain, Mobility, Incontinence, and Sexual Function?

Background: En bloc resection for treatment of sacral tumors is the approach of choice for patients with resectable tumors who are well enough to undergo surgery, and studies describe patient survival, postoperative complications, and recurrence rates associated with this treatment. However, most of these studies do not provide patient-reported functional outcomes other than binary metrics for bowel and bladder function postresection.

Questions/purposes: The purpose of this study was to use validated patient-reported outcomes tools to compare quality of life based on level of sacral resection in terms of (1) physical and mental health; (2) pain; (3) mobility; and (4) incontinence and sexual function.

Prior abdominal surgery is associated with an increased risk of postoperative complications after anterior lumbar interbody fusion.

Study Design: Retrospective medical record review.

Objective: The purpose of this study was to determine whether a history of abdominal/pelvic surgery confers an increased risk of retroperitoneal anterior approach-related complications when undergoing anterior lumbar interbody fusion.

Summary Of Background Data: As anterior lumbar interbody fusion gains popularity, both anterior retroperitoneal approach have become increasingly used.