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Optimized Enrichment of Murine Blood-Brain Barrier Vessels with a Critical Focus on Network Hierarchy in Post-Collection Analysis
No full textCerebrovascular networks contain a unique region of interconnected capillaries known as the blood–brain barrier (BBB). Positioned between upstream arteries and downstream veins, these microvessels have unique structural features, such as the absence of vascular smooth muscle cells (vSMCs) and a relatively thin basement membrane, to facilitate highly efficient yet selective exchange between the circulation and the brain interstitium. This vital role in neurological health and function has garnered significant attention from the scientific community and inspired methodology for enriching BBB capillaries. Extensive characterization of the isolates from such protocols is essential for framing the results of follow-on experiments and analyses, providing the most accurate interpretation and assignment of BBB properties. Seeking to aid in these efforts, here we visually screened output samples using fluorescent labels and found considerable reduction of non-vascular cells following density gradient centrifugation (DGC) and subsequent filtration. Comparatively, this protocol enriched brain capillaries, though larger diameter vessels associated with vSMCs could not be fully excluded. Protein analysis further underscored the enrichment of vascular markers following DGC, with filtration preserving BBB-associated markers and reducing – though not fully removing – arterial/venous contributions. Transcriptional profiling followed similar trends of DGC plus filtration generating isolates with less non-vascular and non-capillary material included. Considering vascular network hierarchy inspired a more comprehensive assessment of the material yielded from brain microvasculature isolation protocols. This approach is important for providing an accurate representation of the cerebrovascular segments being used for data collection and assigning BBB properties specifically to capillaries relative to other regions of the brain vasculature.National Heart, Lung, and Blood Institute, F31HL168946, R01HL159512, R01HL146596, American Heart Association, 23PRE1025483, 19TPA34910121, National Institute of Neurological Disorders and Stroke, R01NS105807.https://www.nature.com/articles/s41598-025-99364-
Reflections of Her: Responding to Objectification of Women through Music, Art, and Identity
No full textThis introductory essay argues that this objectification of women is not a relic of the past, but an evolving system that adapts to new cultural contexts, while perpetually reinforcing long-standing inequities. At the same time, this introduction will also reveal the complexity and ambiguity inherent in the concept of objectification, making it hard to arrive at a singular definition and, therefore, underscoring the need for its critical interrogation. This essay will also explore the consequences of objectifying women—taking into consideration the limitations of efforts to disrupt this cycle—while also exploring the possibilities for resistance, redefinition, and the need to center women’s voices in cultural narratives
"Watch what he chews": The maternal burden for lead poisoning in Baltimore, MD
No full textThis master’s thesis takes a gendered lens in the examination of who has been historically blamed for Baltimore, Maryland’s lead poisoning epidemic. Using mixed qualitative methods, I investigate how the framing of lead poisoning as a “slum” and “minority” problem in newspaper media contributed to harmful class-based and racialized narratives of maternal responsibility that painted the mothers of leadpoisoned children as “careless,” “ignorant,” and “neglectful.” Such a form of scapegoating places the burden of preventing lead exposure on mothers, increasing their household labor, and overlooks broader contributors, such as lead companies and the inaction of state entities. This analysis highlights the need to challenge these narratives and reframe Baltimore’s lead poisoning epidemic to shift away from the individualization of responsibility, contributing to more equitable and intersectional environmental health discourse
To Make the World Better: The Woman's Era and Intersectionality in Turn of the Century Black Press Publications
No full textThis thesis explores The Woman’s Era, the first national newspaper owned, managed, and published by and for African American women. Built upon traditions of Black journalism, literature, and community uplift throughout the century, African American clubwomen carved out a space in a male-dominated field that often resisted their presence. From March 1894 to January 1897, contributors and readers from across the nation shared their thoughts and activities relating to African American social concerns of the late nineteenth century. Drawing from their own experience with both gendered and racial oppression, African American clubwomen combated social ills through community building and social action in a time of ever-increasing racial violence and political, economic, and social discrimination. This thesis showcases the vital role of The Woman’s Era as a platform for African American women’s voices, and details how the newspaper expanded and enhanced opportunities to uplift club women and their communities through gender and racial work
Land Cover and Change Map Accuracy Assessment and Area Estimation Good Practices Protocol
No full textThe main purpose of these community good practice guidelines is to encourage correct implementation of land cover map accuracy assessment and area estimation methods by map producers and to enable map users to correctly interpret the provided map accuracy information. To do so, we provide an overview of key principles of accuracy assessment (section 2.2), recommend specific methods for various components of accuracy assessment published in high quality peer-reviewed studies, and point to potential misapplications of the presented methods that should be avoided.https://pure.iiasa.ac.at/id/eprint/20873/1/CEOS_WGCV_LPV_Land_Cover_protocol_Sept2025_V1.pd
FRACTAL MAP GENERATORS: DEEP STRUCTURES FOR MULTI-SCALE TILE MAPS
No full textExplains neighbor-finding algorithms for high-resolution fractal maps generated (from lower-resolution hand-crafted maps) by various geometries of recursive subdivision. Proposes GIS concepts as a second pillar (with Computer Science) for developing game engines and user interfaces implementing multi-scale tiles (at or below the interaction layer).The evolution from flat square-tile games to flat hex-tile games was an enormous step forward for computer gaming. Transitioning to flat maps with hierarchical hidden structure and/or to deep maps with multi-scalar surface characteristics could be equally significant. Fractal map generators provide a procedural way to produce both. This paper presents the key algorithms for the challenging problem of neighbor-finding in hierarchical coordinate systems. Code and examples are provided in a sequence of increasing difficulty, for Fractal Map Generators with branching-factors (aperture) of 2, 3, 4, 9, and 7 (in that order). This project demonstrates that the rotational drift for fractal hexagonal tiling at aperture seven is 1/3 radians (~ 19.09859 degrees). High resolution fractal hex maps can be generated from low resolution hand-crafted maps, allowing for the combination of recognizable features at the macro scale, and re-playability on the micro scale. Potential multi-scalar game play is built into a single tree data structure. High-interest areas can be represented in unlimited detail, while low-interest areas stay at a lower level of detail, minimizing computational demands. When applied at the interaction level, multi-scalar tiles may improve the UX by enhancing focus on areas of higher relative importance.
Key Words
Fractal Map, Map Generator, Iterated Function System, Region-of-Interest (ROI) rendering, foveation, multi-resolution tiling, multi-scale FEM, replayability, GIS and games, quadtree, bi-tree, tri-tree, nine-tree, hex-tree, Level-of-Detail (LOD) Managementhttps://sites.google.com/view/fractalmapgenerators/hom
Formal Verification of Isothermal Chemical Reactors
No full textChemical reactors are dynamic systems that can be described by systems of ordinary differential equations (ODEs). Reactor safety, regulatory compliance, and economics depend on whether certain states are reachable by the reactor, and are generally assessed using numerical simulation. In this work, we show how differential dynamic logic (dL), as implemented in the automated theorem prover KeYmaera X, can be used to symbolically determine reachability in isothermal chemical reactors, providing mathematical guarantees that certain conditions are satisfied (for example, that an outlet concentration never exceeds a regulatory threshold). First, we apply dL to systems whose dynamics can be solved in closed form, such as first-order reactions in batch reactors, proving that such reactors cannot exceed specified concentration limits. We extend this method to reaction models as complex as Michaelis-Menten kinetics, whose dynamics require approximations or numerical solutions. In all cases, proofs are facilitated by identification of invariants; we find that conservation of mass is both a principle proved from the ODEs describing mass action kinetics as well as a useful relationship for proving other properties. Useful invariants for continuous stirred tank reactors (CSTRs) were not found, which limited the complexity of reaction networks that could be proved with dL. While dL provides an interesting symbolic logic approach for reachability in chemical reactions, the bounds we obtained are quite broad relative to those typically achieved via numerical reachability analyses.Funding was provided by UMBC startup funds.http://arxiv.org/abs/2509.0113
A Comprehensive Guide to Multiset Canonical Correlation Analysis and its Application to Joint Blind Source Separation
No full textMultiset Canonical Correlation Analysis (mCCA), also called Generalized Canonical Correlation Analysis (GCCA), is a technique to identify correlated variables across multiple datasets, which can be used for feature extraction in fields like neuroscience, cross-language information retrieval, and recommendation systems, among others. Besides its wide use, there is still a lack of comprehensive understanding of its theory and implementation with different objective functions all under one umbrella. In this paper, we review the five commonly used mCCA methods sumcor, maxvar, minvar, genvar, and ssqcor. We provide a concise overview of their optimization problems along with their solutions and pseudocodes. After this, we discuss the application of mCCA for estimating underlying latent components in the Joint Blind Source Separation (JBSS) problem and propose the source identification conditions of the different mCCA methods, i.e., the conditions under which they are able to achieve JBSS. We substantiate the proposed theoretical conditions with numerical results and test the statistical efficiency of the methods for finite samples. We observe in our experiments that genvar appears to have the least restrictive source identification conditions and to be more statistically efficient that the other methods. This suggests that genvar is generally the best-performing mCCA method for JBSS except for special cases, which is an important finding, as the most commonly used mCCA methods are maxvar and sumcor.This work was supported by grant NSF 2316420https://ieeexplore.ieee.org/document/1121741
Benchmarking LLMs for Real-World Applications: From Numerical Metrics to Contextual and Qualitative Evaluation
No full textThe evaluation of large language models (LLMs) has traditionally relied on static benchmarks that prioritize performance metrics such as accuracy, precision, BLEU and standardized tests. However, these metrics frequently fail to capture the deeper reasoning, consistency, and real-world applicability of these models. This paper critically examines the limitations of the current benchmarks and preliminarily introduces a practical, context-sensitive framework to qualitatively evaluate LLMs. Through two case studies, which include one for medical diagnosis and the other for traffic engineering, we highlight key shortcomings in existing evaluation approaches. Despite achieving accuracy of 92% in diagnosing diseases and solving multi-step reasoning tasks in the traffic engineering case with 62% accuracy, the evaluated LLM displayed critical gaps, such as overlooking ethical considerations, practical constraints, and failing to maintain consistency across varied prompts. Expert evaluations further revealed issues in reasoning transparency and technical feasibility. This might raise questions about trust in the applicability of LLM systems. By emphasizing domain-specific tasks, expert involvement, and consistency analysis, this study advocates for a paradigm shift in how we benchmark LLMs. The findings underline the urgent need for more nuanced evaluation frameworks to ensure LLMs can reliably support complex, real-world decision-making.https://www.authorea.com/users/884736/articles/1264895-benchmarking-llms-for-real-world-applications-from-numerical-metrics-to-contextual-and-qualitative-evaluatio
Roles of RNA Structures in the Genome Translation of (+) Sense RNA Viruses
No full textPositive (+) sense RNA viruses include many important pathogens that exploit noncanonical translation mechanisms to express their genomes within the host cells. Unlike DNA or negative (-) sense RNA viruses, (+) sense RNA viruses can directly function as mRNAs, even though they lack typical features of host mRNAs, such as the 5' cap structure required for canonical translation initiation. Instead, they exploit structured RNA elements to recruit host translational machinery without the 5' cap, bypassing the canonical translation initiation mechanism. Prominent examples include internal ribosome entry sites (IRESs) and 3' cap-independent translation enhancers (3' CITEs). These RNA modules facilitate translation initiation by recruiting the ribosomal subunits, either directly or through initiation factors, and mediating long-range RNA-RNA interactions. Other regulatory motifs, such as frameshifting signals, allow the ribosome to shift reading frames to regulate protein output. All these RNA elements function through RNA-protein interactions and often utilize host and virus-encoded proteins to hijack the host’s translational apparatus. Over the past several years, various structural biology approaches, including biochemical and enzymatic probing, X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryogenic electron microscopy (cryo-EM), have revealed the unique structural roles of these viral RNA elements and their protein complexes. Although a few structures of IRES and CITE domains have been solved through these methods, the structures of these RNA elements and their structure-function relationship have remained largely unknown. This review discusses the current understanding of translation-related RNA structures in (+) sense RNA viruses, the critical RNA-protein interactions they mediate, and various structural biology approaches used to study them. Since the genome of these viruses serves as a template for two mutually exclusive virological processes, namely genome translation and replication, the review also discusses how viruses can utilize RNA structure-based strategies to regulate the switch between genome translation and replication, highlighting future directions for exploring these fundamental virological processes to develop antiviral therapeutics able to combat diseases caused by these pathogens.This research was funded by the National Institutes of Health (NIH)—National Institute of General Medical Sciences (NIGMS), MIRA R35GM150869.https://www.mdpi.com/1999-4915/17/11/140