Biology subjects

Krishnamurthy, A.

Publications and source records attributed to Krishnamurthy, A..

9 recordsLinked to original sources

bioRxiv2026

Modeling Particle Transport In Biomedical Flows Using Implicit Geometry Representations

Computational analysis of physiological and biomedical systems necessitate efficient geometry representations for high fidelity model predictions, including patient or device specificity. Particle-based Lagrangian computational approaches comprise a valuable approach to gain insights from quantitative velocity and pressure data from computational models. Examples include particle dynamics and transport in human vasculature for diseases such as stroke, thrombosis, and embolisms; and modern targeted drug delivery systems in the vascular network and respiratory airways. However, current particle simulation approaches can bear significant computational expense that scales with both number of particles and background fluid mesh resolution. A significant determinant of this computational expense is the contact resolution between particles and anatomically realistic vessel wall. Here, we develop an efficient particle dynamics model that leverages an implicit representation of real anatomical features using a signed distance field to efficiently resolve particle-wall contact. We outline the underlying algorithmic details, followed by a systematic illustration of performance and accuracy using simplified and analytically defined geometries and flow fields. Subsequently, we present a representative simulation of embolic particles along a human vascular segment where we compare our distance field-based approach against classical wall-contact checks based on assessing particle boundary intersection with triangulated surface mesh. Our approach transforms the underlying Lagrangian contact detection operation into an equivalent Eulerian operation, significantly speeding up bulk particle dynamics computations without significantly impacting accuracy or geometric fidelity.

bioengineering↗

bioRxiv2025

Dose-dependent NFI regulation of progenitor lifespan and output underlying human neocortical malformation

Nuclear Factor I (NFI) misexpressions in humans are associated with severe brain malformations, yet the underlying mechanisms remain poorly understood. Here we show that NFIs regulate the broad lineage progression and lifespan of radial glial progenitors (RGPs), and consequently neocortical development in a dose-dependent manner. Human cerebral organoids carrying patient-mimicking NFI mutations exhibit expression level-dependent bidirectional impairments in RGP temporal development, coinciding with patient phenotypes. In mouse models, selective removal of NFIs leads to a dramatic protraction of RGP lineage progression and lifespan, excessive progeny output, and neocortical overgrowth and abnormal folding, whereas overexpression of NFIs accelerates RGP lineage progression, resulting in developmental stage-dependent precocious productions of diverse neural progenies. Moreover, NFIs exhibit a positive auto-regulation and progressive increase in expression, and regulate distinct temporal-specific targets underlying RGP lineage progression. These results suggest that NFIs act as evolutionarily conserved key global temporal regulators of RGP lineage progression and neocortical development. HIGHLIGHTSO_LINFIs affect human RGP temporal development coinciding with patient phenotypes. C_LIO_LINFI removal protracts RGP lineage progression and lifespan with excessive progeny output. C_LIO_LINFI overexpression accelerates RGP lineage progression with precocious progeny output. C_LIO_LINFIs regulate distinct temporal-specific targets underlying RGP lineage progression. C_LI

neuroscience↗

bioRxiv2025

Computational Modeling Of Immersed Non-spherical Bodies In Viscous Flows To Study Embolus Hemodynamics Interactions For Large Vessel Occlusion Stroke.

Interactions of particles with unsteady non-linear viscous flows has widespread implications in physiological and biomedical systems. One key application where this plays a fundamental role is in the mechanism and etiology of embolic strokes. Specifically, there is a need to better understand how large occlusive emboli traverse complex vascular geometries, and block a vessel disrupting blood supply. Existing modeling approaches resort to key simplifications in terms of embolic particle shape, size, and their coupling to fluid flow. Here, we devise a novel computational model for resolving embolus-hemodynamics interactions for large non-spherical emboli approaching near occlusive regimes in anatomically real vascular segment. The formulation relies on extending an immersed finite element approach, coupled with a six degree-of-freedom particle dynamics model. The geometric complexities and their manifestation in embolus-flow and embolus-wall interactions are handles using a parametric shape representation, and projection of vessel signed distance fields on the particle boundaries. We illustrate our methodology and algorithmic details, as well as present examples of benchmark cases and convergence of our technique. Thereafter, we demonstrate a parametric study of large emboli for LVO strokes, showing that our methodology can capture the non-linear tumbling dynamics of emboli originating form their interactions with the flow and vessel walls; and resolve near-occlusive scenarios involving lubrication effects around the embolus and flow re-routing to non-occludes branches. This is a key methodological advancement in stroke modeling, as to the best of our knowledge this is the first modeling framework for LVO stroke and occlusion biofluid mechanics. Finally, even though we present our framework from the perspective of LVO strokes, the methodology as developed is broadly generalizable to two-way coupled fluid-particle interaction in unsteady viscous flows for a wide range of applications.

bioengineering↗

bioRxiv2024

Cerebellar output neurons impair non-motor behaviors by altering development of extracerebellar connectivity

The capacity of the brain to compensate for insults during development depends on the type of cell loss, whereas the consequences of genetic mutations in the same neurons are difficult to predict. We reveal powerful compensation from outside the cerebellum when the excitatory cerebellar output neurons are ablated embryonically and demonstrate that the minimum requirement for these neurons is for motor coordination and not learning and social behaviors. In contrast, loss of the homeobox transcription factors Engrailed1/2 (EN1/2) in the cerebellar excitatory lineage leads to additional deficits in adult learning and spatial working memory, despite half of the excitatory output neurons being intact. Diffusion MRI indicates increased thalamo-cortico-striatal connectivity in En1/2 mutants, showing that the remaining excitatory neurons lacking En1/2 exert adverse effects on extracerebellar circuits regulating motor learning and select non-motor behaviors. Thus, an absence of cerebellar output neurons is less disruptive than having cerebellar genetic mutations.

neuroscience↗

bioRxiv2024

Successful Cardiac Resynchronization Therapy Reduces Negative Septal Work in Patient-Specific Models of Dyssynchronous Heart Failure

In patients with dyssynchronous heart failure (DHF), cardiac conduction abnormalities cause the regional distribution of myocardial work to be non-homogeneous. Cardiac resynchronization therapy (CRT) using an implantable, programmed biventricular pacemaker/defibrillator, can improve the synchrony of contraction between the right and left ventricles in DHF, resulting in reduced morbidity and mortality and increased quality of life. Since regional work depends on wall stress, which cannot be measured in patients, we used computational methods to investigate regional work distributions and their changes after CRT. We used three-dimensional multi-scale patient-specific computational models parameterized by anatomic, functional, hemodynamic, and electrophysiological measurements in eight patients with heart failure and left bundle branch block (LBBB) who received CRT. To increase clinical translatability, we also explored whether streamlined computational methods provide accurate estimates of regional myocardial work. We found that CRT increased global myocardial work efficiency with significant improvements in non-responders. Reverse ventricular remodeling after CRT was greatest in patients with the highest heterogeneity of regional work at baseline, however the efficacy of CRT was not related to the decrease in overall work heterogeneity or to the reduction in late-activated regions of high myocardial work. Rather, decreases in early-activated regions of myocardium performing negative myocardial work following CRT best explained patient variations in reverse remodeling. These findings were also observed when regional myocardial work was estimated using ventricular pressure as a surrogate for myocardial stress and changes in endocardial surface area as a surrogate for strain. These new findings suggest that CRT promotes reverse ventricular remodeling in human dyssynchronous heart failure by increasing regional myocardial work in early-activated regions of the ventricles, where dyssynchrony is specifically associated with hypoperfusion, late systolic stretch, and altered metabolic activity and that measurement of these changes can be performed using streamlined approaches.

bioengineering↗

bioRxiv2023

Engrailed transcription factors direct excitatory cerebellar neuron diversity and survival

The excitatory neurons of the three cerebellar nuclei (eCN) form the primary output for the cerebellar circuit. The medial eCN (eCNm) were recently divided into molecularly defined subdomains in the adult, however how they are established during development is not known. We define molecular subdomains of the eCNm using scRNA-seq and spatial expression analysis and show they evolve during embryogenesis to resemble the adult. Furthermore, the eCNm is transcriptionally divergent from the rest of the eCN by E14.5. We previously showed that loss of the homeobox genes En1 and En2 leads to death of a subset of embryonic eCNm. We demonstrate that mutation of En1/2 in embryonic eCNm results in cell death of specific posterior eCNm molecular subdomains and loss of TBR2 (EOMES) expression in an anterior subdomain, as well as reduced synaptic gene expression. We further reveal a similar function for EN1/2 in mediating TBR2 expression, neuron differentiation and survival in the two other cerebellar excitatory neuron types. Thus, our work defines embryonic eCNm molecular diversity and reveals conserved roles for EN1/2 in the cerebellar excitatory neuron lineage.

developmental biology↗

bioRxiv2022

Distinct contact guidance mechanisms in single endothelial cells and in monolayers

In many tissues, cell shape and orientation are controlled by a combination of internal and external biophysical cues. Anisotropic substrate topography is a ubiquitous cue that leads to cellular elongation and alignment, a process termed contact guidance, whose underlying mechanisms remain incompletely understood. Additionally, whether contact guidance responses are similar in single cells and in cellular monolayers is unknown. Here, we address these questions in vascular endothelial cells (ECs) that in vivo form a monolayer that lines blood vessels. Culturing single ECs on microgrooved substrates that constitute an idealized mimic of anisotropic basement membrane topography elicits a strong, groove depth-dependent contact guidance response. Interestingly, this response is greatly attenuated in confluent monolayers. While contact guidance in single cells is principally driven by persistence bias of cell protrusions in the direction of the grooves and is surprisingly insensitive to actin stress fiber disruption, cell shape and alignment in dense EC monolayers are driven by the organization of the basement membrane secreted by the cells, which leads to a loss of interaction with the microgrooves. The findings of distinct contact guidance mechanisms in single ECs and in EC monolayers promise to inform strategies aimed at designing topographically patterned endovascular devices.

cell biology↗

bioRxiv2021

Dug: A Semantic Search Engine Leveraging Peer-Reviewed Literature to Span Biomedical Data Repositories

MotivationAs the number of public data resources continues to proliferate, identifying relevant datasets across heterogenous repositories is becoming critical to answering scientific questions. To help researchers navigate this data landscape, we developed Dug: a semantic search tool for biomedical datasets utilizing evidence-based relationships from curated knowledge graphs to find relevant datasets and explain why those results are returned. ResultsDeveloped through the National Heart, Lung, and Blood Institutes (NHLBI) BioData Catalyst ecosystem, Dug has indexed more than 15,911 study variables from public datasets. On a manually curated search dataset, Dugs total recall (total relevant results/total results) of 0.79 outperformed default Elasticsearchs total recall of 0.76. When using synonyms or related concepts as search queries, Dug (0.36) far outperformed Elasticsearch (0.14) in terms of total recall with no significant loss in the precision of its top results. Availability and ImplementationDug is freely available at https://github.com/helxplatform/dug. An example Dug deployment is also available for use at https://search.biodatacatalyst.renci.org/. Contactawaldrop@rti.org or scox@renci.org

bioinformatics↗

bioRxiv2020

NuMorph: tools for cellular phenotyping in tissue cleared whole brain images

Tissue clearing methods allow every cell in the mouse brain to be imaged without physical sectioning. However, the computational tools currently available for cell quantification in cleared tissue images have been limited to counting sparse cell populations in stereotypical mice. Here we introduce NuMorph, a group of image analysis tools to quantify all nuclei and nuclear markers within the mouse cortex after tissue clearing and imaging by a conventional light-sheet microscope. We applied NuMorph to investigate two distinct mouse models: a Topoisomerase 1 (Top1) conditional knockout model with severe neurodegenerative deficits and a Neurofibromin 1 (Nf1) conditional knockout model with a more subtle brain overgrowth phenotype. In each case, we identified differential effects of gene deletion on individual cell-type counts and distribution across cortical regions that manifest as alterations of gross brain morphology. These results underline the value of 3D whole brain imaging approaches and the tools are widely applicable for studying 3D structural deficits of the brain at cellular resolution in animal models of neuropsychiatric disorders.

neuroscience↗