Biology subjects

Williams, S. C.

Publications and source records attributed to Williams, S. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatial collinearity constrains multivariate molecular-enriched network estimation

Analyses of neuroimaging data increasingly leverage the distribution of neurotransmitter receptors derived from Positron Emission Tomography (PET) to bridge the gap between micro- and macro-scale brain function. However, these receptor maps are highly spatially overlapping which can give rise to interpretive and analytical challenges. Here, we systematically investigate the impact of spatial collinearity among PET maps in the context of Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), a method that uses receptor maps as spatial regressors to derive subject-level molecular-enriched functional connectivity networks. Exhaustive combinatorial analysis across 19 receptor and transporter maps showed that collinearity scales rapidly with the number of receptors modelled simultaneously, and that this was relatively stable across parcellation scales, reflecting the intrinsic organisation of neurotransmitter systems. Using test-retest fMRI data from the Human Connectome Project, we demonstrate that modelling greater numbers of receptors degrades the reliability of molecular-enriched networks derived from conventional multivariate REACT models, and that collinearity among receptor maps drives this degradation. An alternative univariate approach, in which each receptor is modelled independently, yielded more reliable networks and, when applied to a within-subjects study of LSD compared to placebo, better recovered the role of the 5HT-2A receptor in LSDs neural effects. These findings identify spatial collinearity as a fundamental constraint on multivariate molecular-enriched network estimation and support univariate modelling as a more robust default for this class of analysis.

neuroscience↗

bioRxiv2025

Microbiome-behavior coupling shapes infant adaptation to early maternal unpredictability

We asked whether infant microbiome composition, together with infants behavioral responses to early maternal unpredictability, can offer novel mechanistic insights into behavioral phenotypic variation in human development. Maternal unpredictability was computed as the entropy rate of transitions among maternal sensory signals during naturalistic mother-infant interaction (n=256 dyads; 2-6 months). Infant visual orienting behavior (VOB) was indexed by infants simultaneous gaze shifts to and from the mother. Higher maternal unpredictability predicted more frequent VOB shifts, indicating a mature-for-age profile, and longitudinally forecast poorer inhibitory control at 19-28 months. A subgroup of infants with high maternal unpredictability and high VOB had inhibitory control outcomes closer to those of infants who experienced low maternal unpredictability, suggesting VOB strategy might buffer against the effects of high maternal unpredictability. In participants with metagenomic data (n=93), VOB was associated with taxonomic and functional gut microbial profiles along a Bifidobacterium breve to Bifidobacterium longum axis. Neuroactive gene-set enrichment analysis linked VOB to increase in tryptophan synthesis and glutamate synthesis genes. In contrast, maternal unpredictability showed depletions of GABA and tryptophan synthesis in the unique-effects model and, when VOB and the maternal unpredictability by VOB term were included, enrichment of acetate synthesis and quinolinic acid degradation. Notably, the maternal unpredictability by VOB interactions for tryptophan and glutamate were negative, indicating that the VOB-pathway coupling attenuates as unpredictability increases. Together, these findings support a framework in which maternal unpredictability is the environmental challenge, infant VOB expresses the behavioral strategy, and microbial metabolism modulates whether that strategy is biochemically feasible. TeaserInfant gut microbiome is linked to infant behavioral responses to maternal unpredictability, which in turn impacts how they learn to control their actions.

neuroscience↗

bioRxiv2025

Cross-Molecular Active Learning for the Discovery of Antimicrobial Polyacrylamides

Antimicrobial resistance poses an urgent and increasing threat to global health. The development of new antimicrobials is crucial. Synthetic copolymers are attractive as a potential solution, because they can be produced at scale and designed to mimic antimicrobial peptides and act as broad-spectrum antimicrobials capable of evading resistance mechanisms. This work leverages a cross-molecular machine learning pipeline, trained on antimicrobial peptides, to develop potent antimicrobial polymers to combat Escherichia coli, which were then synthesized and validated experimentally. One candidate copolymer was further characterized and shown to permeabilize the bacterial membrane, which is associated with decreased resistance. Furthermore, this copolymer demonstrated remarkable synergy in eradicating biofilm-associated E. coli when combined with a first-line clinical drug regimen, reducing the amount needed to eradicate bacteria in biofilms by three orders of magnitude. These results demonstrate promise for potentiating antibacterial activity of currently available antibiotics, treating serious and complicated infections, and combatting antimicrobial resistance.

microbiology↗

bioRxiv2025

Intranasal sertraline for the investigation of nose-to-brain delivery to mitigate systemic exposure

Antenatal depression, or depression during pregnancy, is a common psychiatric disorder and poses significant risks to both the mother and the fetus. Despite these risks, it is frequently left untreated due to fears of side effects caused by antidepressant medications which cross through the placental barrier. It is therefore desirable to develop formulation strategies to mitigate systemic exposure to relevant drug molecules while maintaining their psychotropic efficacy. In this work, we develop formulations of sertraline, a common antidepressant, to target delivery to the brain through intranasal administration. Formulation engineering enables successful solubilization of sertraline at high concentrations and our lead formulation remains stable at room temperature for months. Using mice, we compare sertraline biodistribution following intranasal administration and standard oral administration. Intranasal administration of our drug product candidate provides comparable brain exposure at half the dose compared to oral treatment and lowers the maximum plasma exposure. These findings suggest that intranasal administration may provide selectivity for drug exposure in the central nervous system over systemic exposure.

pharmacology and toxicology↗

bioRxiv2025

Engineering Sustained-Release Broadly Neutralizing Antibody Formulations

Sustained serum levels of broadly neutralizing antibodies (bnAbs) are crucial for effective passive immunization against infectious diseases as protection persists only while these bnAbs remain at adequate concentrations within the body. Current obstacles, such as poor pharmacokinetics (PK) and burdensome administration, must be overcome to make bnAbs a viable option for pre- and post-exposure prophylaxis. In this work, we explore how a polymer-nanoparticle (PNP) hydrogel depot technology can be engineered to prolong protein delivery. In-vivo studies in mice and rats demonstrate prolonged protein release, and modeling efforts predict the impact of both the elimination half-life of the active pharmaceutical ingredient and hydrogel depot volume on overall pharmacokinetics. Moreover, flow cytometry characterization reveals that immune cell infiltration into the hydrogel depot can result in faster-than-expected release of antibody cargo on account of active transport via cellular uptake. We then demonstrate that co-formulation of antibodies with an anti-inflammatory agent reduces cellular infiltration and resulting active transport, further extending delivery and pharmacokinetics. Finally, multicompartmental modeling predicts the human PK profiles of clinically relevant HIV bnAbs delivered via subcutaneous hydrogel injection. These findings aid in the development of next generation hydrogel materials that stabilize and slowly release bnAbs for long-term pre-exposure immunoprophylaxis.

bioengineering↗

bioRxiv2025

MegaTrack: a framework for the anatomically accurate and time-efficient virtual dissection and analysis of large-scale tractography datasets

The increasing prevalence of large-scale neuroimaging initiatives has created a need for efficient and anatomically accurate methods for analysing tractography data. Here, we present MegaTrack, a framework designed to combine the anatomical precision of manual dissections with the efficiency required for big data analysis. At its core, MegaTrack operates by normalising individual tractography datasets to a standard space, concatenating them into a single "mega" tractography dataset the user manually dissects before automatically extracting subject-specific tracts and metrics in native space. This approach permits identifying and extracting tracts not yet available in existing templates or automatic dissection tools. We validated this approach using multiple datasets and applications. Comparison with individual manual dissections showed high spatial agreement (weighted dice coefficient > 0.95) and strong correlations in tract-specific metrics (R2 > 0.9). In a longitudinal dataset, MegaTrack demonstrated improved reproducibility across time points and higher inter-rater reliability compared to manual dissections. In a motor neuron disease cohort, MegaTrack replicated known group differences in corticospinal tract microstructure with comparable sensitivity to manual dissections (p = 0.001) but with significantly reduced processing time. Finally, we showcase MegaTracks scalability by creating a comprehensive white matter atlas from 140 healthy adults and demonstrate its application for lesion analysis in stroke patients. This framework is accompanied by an interactive online tool that allows users to explore these atlases and perform customised lesion analyses. The MegaTrack framework is a time-efficient solution for the anatomically precise analysis of large tractography datasets, enabling the rapid simultaneous dissection of multiple subjects while preserving individual anatomical features. The frameworks ability to efficiently process large datasets makes it an excellent tool for generating training data for machine learning and deep learning algorithms in tractography analysis. This approach has broad applications in both research and clinical settings, from group comparisons to personalised lesion mapping, and can significantly contribute to the development of advanced automated tractography methods.

neuroscience↗

bioRxiv2025

Preventing peritendinous adhesions using lubricious supramolecular hydrogels

Of the 1.5 million emergency room visits each year in the United States due to flexor tendon injuries in the hand, over 30-40% result in peritendinous adhesions which can limit range of motion (ROM) and severely impact an individuals quality of life. Adhesions are fibrous scar-like tissues which can form between adjacent tissues in the body in response to injury, inflammation, or during normal healing following surgery. Currently, there is no widespread solution for adhesion prevention in the delicate space of the digit while allowing a patient full ROM quickly after surgery. There is a clear clinical need for a material capable of limiting adhesion formation which is simple to apply, does not impair healing, remains at the application site during motion and initial inflammation (days - weeks), and leaves tendon glide unencumbered. In this work, we developed dynamically crosslinked, bioresorbable supramolecular hydrogels as easy-to-apply lubricious barriers to prevent the formation of peritendinous adhesions. These hydrogels exhibit excellent long-term stability, injectability, and thermally stable viscoelastic properties that allow for simple storage and facile application. We evaluated interactions at the interface of the hydrogels and relevant tissues, including human tendon and skin, in shear and extensional stress modes and demonstrated a unique mechanism of adhesion prevention based on maintenance of a lubricious hydrogel barrier between tissues. Ex vivo studies show that the hydrogels did not impair the gliding behavior nor mechanical properties of tendons when applied in cadaveric human hands following clinically relevant flexor tendon repair. We further applied these hydrogels in a preclinical rat Achilles tendon injury model and observed prolonged local retention at the repair site as well as improved recovery of key functional metrics, including ROM and maximal dorsiflexion. Further, these hydrogels were safe and did not impair tendon strength nor healing compared to the current standard of care. These dynamic, biocompatible hydrogels present a novel solution to the significant problem of peritendinous adhesions with clear translational potential.

bioengineering↗

bioRxiv2024

Polyacrylamide-based Antimicrobial Copolymers Immune to Typical Resistance Mechanisms to Replace or Rescue Antibiotics

Antibiotics save countless lives each year and have dramatically improved human health outcomes since their introduction in the 20th century. Unfortunately, bacteria are now developing resistance to antibiotics at an alarming rate, with many new strains of "superbugs" showing simultaneous resistance to multiple classes of antibiotics. To mitigate the global burden of antimicrobial resistance, we must develop new antibiotics that are broadly effective, safe, and highly stable for the purpose of global access. In this manuscript, we report the development of polyacrylamide-based copolymers as a novel class of broad-spectrum antibiotics with efficacy against several critical pathogens. We demonstrate that these copolymer drugs are selective for bacteria over mammalian cells, indicating a favorable safety profile. We show that they kill bacteria through a membrane disruption mechanism, which allows them to overcome traditional mechanisms of antimicrobial resistance. Finally, we demonstrate their ability to rehabilitate an existing small-molecule antibiotic that is highly subject to resistance development by improving its potency and eliminating the development of resistance in a combination treatment. This work represents a significant step towards combatting antimicrobial resistance.

bioengineering↗

bioRxiv2024

Generation of an inflammatory niche in an injectable hydrogel depot through recruitment of key immune cells improves efficacy of mRNA vaccines

Messenger RNA (mRNA) delivered in lipid nanoparticles (LNPs) rose to the forefront of vaccine candidates during the COVID-19 pandemic due in part to scalability, adaptability, and potency. Yet there remain critical areas for improvements of these vaccines in durability and breadth of humoral responses. In this work, we explore a modular strategy to target mRNA/LNPs to antigen presenting cells with an injectable polymer-nanoparticle (PNP) hydrogel depot technology which recruits key immune cells and forms an immunological niche in vivo. We characterize this niche on a single cell level and find it is highly tunable through incorporation of adjuvants like MPLAs and 3M-052. Delivering commercially available SARS-CoV-2 mRNA vaccines in PNP hydrogels improves the durability and quality of germinal center reactions, and the magnitude, breadth, and durability of humoral responses. The tunable immune niche formed within PNP hydrogels effectively skews immune responses based on encapsulated adjuvants, creating opportunities to precisely modulate mRNA/LNP vaccines for various indications from infectious diseases to cancers.

bioengineering↗

bioRxiv2024

Multi-orientation U-Net for Super-Resolution of Ultra-Low-Field Paediatric MRI

Owing to the high cost of modern MRI systems, their use in clinical care and neurodevelopmental research is limited to hospitals and universities in high income countries. Ultra-low-field systems with significantly lower scanning costs present a promising avenue towards global MRI accessibility, however their reduced SNR compared to 1.5 or 3T systems limits their applicability for research and clinical use. In this paper, we describe a deep learning-based super-resolution approach to generate high-resolution isotropic T2-weighted scans from low-resolution paediatric input scans. We train a multi-orientation U-Net, which uses multiple low-resolution anisotropic images acquired in orthogonal orientations to construct a super-resolved output. Our approach exhibits improved quality of outputs compared to current state-of-the-art methods for super-resolution of ultra-low-field scans in paediatric populations. Crucially for paediatric development, our approach improves reconstruction of deep brain structures with the greatest improvement in volume estimates of the caudate, where our model improves upon the state-of-the-art in: linear correlation (r = 0.94 vs 0.84 using existing methods), exact agreement (Lins concordance correlation = 0.94 vs 0.80) and mean error (0.05 cm3 vs 0.36 cm3). Our research serves as proof-of-principle of the viability of training deep-learning based super-resolution models for use in neurodevelopmental research and presents the first model trained exclusively on paired ultra-low-field and high-field data from infants.

neuroscience↗

bioRxiv2023

Survey of white-footed mice in Connecticut, USA reveals low SARS-CoV-2 seroprevalence and infection with divergent betacoronaviruses

Diverse mammalian species display susceptibility to and infection with SARS-CoV-2. Potential SARS-CoV-2 spillback into rodents is understudied despite their host role for numerous zoonoses and human proximity. We assessed exposure and infection among white-footed mice (Peromyscus leucopus) in Connecticut, USA. We observed 1% (6/540) wild-type neutralizing antibody seroprevalence among 2020-2022 residential mice with no cross-neutralization of variants. We detected no SARS-CoV-2 infections via RT-qPCR, but identified non-SARS-CoV-2 betacoronavirus infections via pan-coronavirus PCR among 1% (5/468) of residential mice. Sequencing revealed two divergent betacoronaviruses, preliminarily named Peromyscus coronavirus-1 and -2. Both belong to the Betacoronavirus 1 species and are [~]90% identical to the closest known relative, Porcine hemagglutinating encephalomyelitis virus. Low SARS-CoV-2 seroprevalence suggests white-footed mice may not be sufficiently susceptible or exposed to SARS-CoV-2 to present a long-term human health risk. However, the discovery of divergent, non-SARS-CoV-2 betacoronaviruses expands the diversity of known rodent coronaviruses and further investigation is required to understand their transmission extent.

ecology↗

bioRxiv2023

The ACE-inhibitor drug captopril inhibits ACN-1 to control dauer formation and aging

The renin-angiotensin-aldosterone system (RAAS) plays a well-characterized role regulating blood pressure in mammals. Pharmacological and genetic manipulation of the RAAS has been shown to extend lifespan in C. elegans, Drosophila, and rodents, but its mechanism is not well defined. Here we investigate the angiotensin-converting enzyme (ACE) inhibitor drug captopril, which extends lifespan in worms and mice. To investigate the mechanism, we performed a forward genetic screen for captopril hypersensitive mutants. We identified a missense mutation that causes a partial loss-of-function of the daf-2 receptor tyrosine kinase gene, a powerful regulator of aging. The homologous mutation in the human insulin receptor causes Donohue syndrome, establishing these mutant worms as an invertebrate model of this disease. Captopril functions in C. elegans by inhibiting ACN-1, the worm homolog of ACE. Reducing the activity of acn-1 via captopril or RNAi promoted dauer larvae formation, suggesting acn-1 is a daf gene. Captopril-mediated lifespan extension xwas abrogated by daf-16(lf) and daf-12(lf) mutations. Our results indicate that captopril and acn-1 control aging by modulating dauer formation pathways. We speculate that this represents a conserved mechanism of lifespan control. Summary StatementCaptopril and acn-1 control aging. By demonstrating they regulate dauer formation and interact with daf genes, including a new DAF-2(A261V) mutant corresponding to a human disease variant, we clarified the mechanism.

developmental biology↗

bioRxiv2022

Phylogeographic reconstruction of the emergence and spread of Powassan virus in the northeastern United States

Powassan virus is an emerging tick-borne virus of concern for public health, but very little is known about its transmission patterns and ecology. Here, we expanded the genomic dataset by sequencing 279 Powassan viruses isolated from Ixodes scapularis ticks from the northeastern United States. Our phylogeographic reconstructions revealed that Powassan virus lineage II was likely introduced or emerged from a relict population in the Northeast between 1940-1975. Sequences strongly clustered by sampling location, suggesting a highly focal geographical distribution. Our analyses further indicated that Powassan virus lineage II emerged in the northeastern U.S. mostly following a south to north pattern, with a weighted lineage dispersal velocity of ~3 km/year. Since the emergence in the Northeast, we found an overall increase in the effective population size of Powassan virus lineage II, but with growth stagnating during recent years. The cascading effect of population expansion of white-tailed deer and I. scapularis populations likely facilitated the emergence of Powassan virus in the northeastern U.S. Significance statementOur work provides important fundamental insights in the local transmission dynamics of an emerging tick-borne pathogen of public health concern. Without the availability of vaccines or specific treatments, prevention of Powassan virus infection is dependent on education and control. We identified that Powassan virus is maintained in highly localized transmission foci that have been maintained for several years, without introductions of new virus clades. This provides both opportunities for better education about high risk areas and effective targeted control in Powassan virus foci with a long lasting impact.

genomics↗

bioRxiv2022

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) is a novel analytical strategy that enriches functional connectivity (FC) information from functional MRI (fMRI) with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the FC analysis. So far, this integrative approach has been used in blood oxygen level-dependent (BOLD) fMRI studies only, providing new insights into the brain mechanisms underlying specific disorders and its response to pharmacological challenges. In this study, we demonstrate that the application of REACT can be further extended to arterial spin labelling (ASL) fMRI. Some of the advantages of this extension include the combination of neurotransmitter specific information provided by molecular imaging with a quantitative marker of neuronal activity, the suitability of ASL for pharmacological MRI (phMRI) studies assessing drug effects on baseline brain function, and the possibility to acquire images that are not affected by susceptibility artifacts in the regions linked to major neurotransmitter systems. In this work, we tested the feasibility of applying REACT to resting state ASL fMRI and compared the molecular-enriched FC maps derived from ASL data with those derived from BOLD data. We applied REACT to high-resolution, whole-brain simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL- and BOLD-based FC maps related to six molecular systems, including the transporters of dopamine, noradrenaline, serotonin and vesicular acetylcholine, and the GABA-A and mGlu5 receptors. We then compared the ASL and BOLD FC maps in terms of spatial similarity, using the Dice Similarity Index and the voxel-wise spatial correlation. On a data subsample (N=19) we also evaluated the test-retest reproducibility of each modality using the regional intraclass correlation coefficient, and compared the two modalities. Our results showed robust spatial patterns of molecular-enriched functional connectivity for both modalities, moderate to high similarity between BOLD- and ASL-derived FC maps and mixed results in terms of reproducibility (i.e., none of the modalities outperformed the other). Overall, our findings show that the ASL signal is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits. Considering the more direct link of ASL imaging with neuronal acrivity compared to BOLD and its suitability for phMRI studies, this new integrative approach could become a valuable asset in clinical studies investigating functional alterations in patients with brain disorders, or in pharmacological studies investigating the effects of new or existing compounds on the brain.

neuroscience↗

bioRxiv2021

Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain

The expansion of neuroimaging techniques over the last decades has opened a wide range of new possibilities to characterize brain dysfunction in several neurological and psychiatric disorders. However, the lack of specificity of most of these techniques, such as magnetic resonance imaging (MRI)-derived measures, to the underlying molecular and cellular properties of the brain tissue poses limitations to the amount of information one can extract to inform precise models of brain disease. The integration of transcriptomic and neuroimaging data, known as imaging transcriptomics, has recently emerged as an indirect way forward to test and/or generate hypotheses about potential cellular and transcriptomic pathways that might underly specific changes in neuroimaging MRI biomarkers. However, the validity of this approach is yet to be examined in-depth. Here, we sought to bridge this gap by performing imaging transcriptomic analyses of the regional distribution of well-known molecular markers, assessed by positron emission tomography (PET), in the healthy human brain. We focused on tracers spanning different elements of the biology of the brain, including neuroreceptors, synaptic proteins, metabolism, and glia. Using transcriptome-wide data from the Allen Brain Atlas, we applied partial least square regression to rank genes according to their level of spatial alignment with the regional distribution of these neuroimaging markers in the brain. Then, we performed gene set enrichment analyses to explore the enrichment for specific biological and cell-type pathways among the genes most strongly associated with each neuroimaging marker. Overall, our findings show that imaging transcriptomics can recover plausible transcriptomic and cellular correlates of the regional distribution of benchmark molecular imaging markers, independently of the type of parcellation used to map gene expression and neuroimaging data. Our data support the plausibility and robustness of imaging transcriptomics as an indirect approach for bridging gene expression, cells and macroscopical neuroimaging and improving our understanding of the biological pathways underlying regional variability in neuroimaging features.

neuroscience↗

bioRxiv2021

Transcriptional and cellular signatures of cortical morphometric similarity remodelling in chronic pain

Chronic pain is a highly debilitating and poorly understood condition. Here, we attempt to advance our understanding of the brain mechanisms driving chronic pain by investigating alterations in morphometric similarity (MS) and corresponding transcriptomic and cellular signatures, in three cohorts of patients with distinct chronic pain syndromes (knee osteoarthritis, low back pain and fibromyalgia). We uncover a novel pattern of cortical MS remodelling involving mostly MS increases in the insula and limbic cortex, which cuts across the boundaries of specific pain syndromes. We show that cortical MS remodelling in chronic pain spatially correlates with the brain-wide expression of genes involved in the glial immune response and neuronal plasticity. Cortical remodelling in chronic pain might involve a disruption of multiple elements of the cellular architecture of the brain. Therefore, multi-target therapeutic approaches tackling both glial activation and neuronal hyperexcitability might better encompass the full neurobiology of chronic pain.

neuroscience↗

bioRxiv2021

A candidate neuroimaging biomarker for detection of neurotransmission-related functional alterations and prediction of pharmacological analgesic response in chronic pain

BackgroundChronic pain is a world-wide clinical challenge. Response to analgesic treatment is limited and difficult to predict. Functional MRI (fMRI) has been suggested as a potential solution. However, while most analgesics target specific neurotransmission pathways, fMRI-based biomarkers are not specific for any neurotransmitter system, limiting our understanding of how they might contribute to predict treatment response. MethodsHere, we sought to bridge this gap by applying Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) to investigate whether neurotransmission-enriched functional connectivity (FC) mapping can provide insights into the brain mechanisms underlying chronic pain and inter-individual differences in analgesic response after a placebo or duloxetine. Chronic knee osteoarthritis (OA) pain patients (n=56) underwent pre-treatment brain scans in two clinical trials. Study 1 (n=17) was a 2-week single-blinded placebo pill trial. Study 2 (n=39) was a 3-month double-blinded randomized trial comparing placebo to duloxetine, a dual serotonin-noradrenaline reuptake inhibitor. ResultsAcross two independent studies, we found that chronic pain OA patients present FC alterations in the FC related to the serotonin (SERT) and noradrenaline (NET) transporters, when compared to age-matched healthy controls. Placebo responders presented with higher pre-treatment dopamine transporter (DAT)-enriched FC than non-responders. Duloxetine responders presented with higher pre-treatment SERT and NET-enriched FC than non-responders. Pre-treatment SERT and NET-enriched FC achieved predictive positive values of duloxetine response up to 85.71%. ConclusionNeurotransmission-enriched FC mapping might hold promise as a new mechanistic-informed biomarker for functional brain alterations and prediction of response to pharmacological analgesia in chronic pain.

neuroscience↗

bioRxiv2021

In vivo multi-parametric manganese-enhanced MRI for detecting senile plaques in rodent models of Alzheimer's disease

Senile plaques are a hallmark of Alzheimers disease (AD) that develop in its earliest stages. Thus, non-invasive detection of these plaques would be invaluable for diagnosis and the development and monitoring of treatments, but this remains a challenge due to their small size. Here, we investigated the utility of manganese-enhanced MRI (MEMRI) for visualizing plaques in transgenic rodent models of AD across two species: 5xFAD mice and TgF344-AD rats. Fourteen mice (eight transgenic, six wild-type) and eight rats (four transgenic, four wild-type) were given subcutaneous injections of MnCl2 and imaged in vivo using a 9.4T Bruker scanner. Susceptibility-weighted images, transverse relaxation rate (R2*) maps, and quantitative susceptibility maps were derived from high-resolution 3D multi-gradient-echo (MGE) data to directly visualize plaques. Longitudinal relaxation rate (R1) maps were derived from MP2RAGE data to measure regional manganese uptake. After scanning, the brains were processed for histology and stained for beta-amyloid (4G8 antibody), iron (Perls), and calcium/manganese (Alizarin Red). MnCl2 improved signal-to-noise ratio (1.55{+/-}0.39-fold increase in MGE images) as expected, although this was not necessary for detection of plaques in the high-resolution images. Plaques were visible in susceptibility-weighted images, R2* maps, and quantitative susceptibility maps, with increased R2* and more positive magnetic susceptibility compared to surrounding tissue. In the 5xFAD mice, most MR-visible plaques were in the hippocampus, though histology confirmed plaques in the cortex and thalamus as well. In the TgF344-AD rats, many more plaques were MR-visible throughout the hippocampus and cortex. Beta-amyloid and iron staining indicate that, in both models, MR visibility was driven by plaque size and iron load. Voxel-wise comparison of R1 maps revealed increased manganese uptake in brain regions of high plaque burden in transgenic animals compared to their wild-type littermates. Interestingly, in contrast to plaque visibility in the high-resolution images, the increased manganese uptake was limited to the rhinencephalon in the TgF344-AD rats (family-wise error (FWE)-corrected p < 0.05) while it was most significantly increased in the cortex of the 5xFAD mice (FWE-corrected p < 0.3). Alizarin Red staining suggests that manganese bound to plaques in 5xFAD mice but not in TgF344-AD rats. Multi-parametric MEMRI is a simple, viable method for detecting senile plaques in rodent models of AD. Manganese-induced signal enhancement can enable higher-resolution imaging, which is key to visualizing these small amyloid deposits. We also present in vivo evidence of manganese as a potential targeted contrast agent for imaging plaques in the 5xFAD model of AD. HighlightsO_LIThis is the first study to use manganese-enhanced MRI (MEMRI) for direct visualization of senile plaques in rodent models of Alzheimers disease, in vivo. C_LIO_LIManganese enhancement is not necessary to detect plaques but improves image contrast and signal-to-noise ratio. C_LIO_LIManganese binds to plaques in 5xFAD mice but not in TgF344-AD rats, demonstrating potential as a targeted contrast agent for imaging plaques in certain models of AD. C_LI

neuroscience↗