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Biology subjects

Johnson, C. L.

Publications and source records attributed to Johnson, C. L..

10 recordsLinked to original sources

Rapid Identification of Infections Directly from Isolates and Clinical Specimens with the MasSpec Pen Technology

The time-consuming nature of conventional bacterial identification methods, coupled with rising resistance to antibiotics, presents a serious challenge in the rapid diagnosis and treatment of patients suffering from severe infection and sepsis. In this study, we demonstrate that the MasSpec Pen (MSPen) technology enables rapid identification of the most frequently occurring bacterial species in human infections. A total of 755 clinical bacterial isolates prospectively collected from pediatric and adult patients were analyzed using the MSPen to create a library of molecular profiles. The mass spectra obtained presented distinct molecular patterns for bacterial species, with high relative abundances of bacterial metabolites and lipids, including unique quinolone signaling molecules in Pseudomonas aeruginosa, phosphoethanolamine (PE) lipids in Enterobacteriaceae, and phosphatidylglycerol (PG) lipids in Staphylococcus species. Logistic and multinomial lasso models using relative abundances or logarithmic-ratio abundance calculations achieved >95% accuracy for Gram stain typing and >92% for species-level identification in isolates. Random forest models yielded comparable performance, reinforcing the robustness of these findings across approaches. Many of the metabolite and lipid predictive features from each isolate classifier were detected when directly analyzing highly infected synovial fluid, tissue, pleural fluid, and breast aspirate specimens from patients. Notably, significant variations in the natural isotopic abundance of specific lipids were observed in infected patient samples, indicating presence of bacterial infection. This study demonstrates the potential of MSPen for the direct identification of bacterial-specific metabolites and lipids in clinical isolates and specimens, offering promise for future advancements in the MSPen technology for rapid bacterial identification. Teaser.MSPen shows potential for rapid, direct identification of bacterial metabolites and lipids, enabling accurate bacterial classification.

microbiology↗

Age and Gender-Dependent Group-Average Brain Biomechanics Models for Traumatic Brain Injury

Experimental studies involving mechanical loading of the human head and brain in vivo are necessarily limited, making computational modeling essential for advancing our understanding of brain biomechanics. Demographic factors such as age and gender are known to influence brain anatomical structures, material properties, and potentially vulnerability to injurious loading. To address this, we construct six group-average brain models stratified by age and gender from a total of 135 subjects, and investigate the mechanical responses of these "group-average brains" using computational simulations. We use Pearson correlations to assess to what degree the group-average models represent individuals within each demographic category, showing strong correlations. Further, our p-value hypothesis test of the first principal strain across the six groups shows significant differences. This study demonstrates that age- and gender-stratified group-average models can effectively represent biomechanical responses of the individuals within the groups, and can reveal meaningful demographic differences that may influence susceptibility to traumatic brain injury. We show that the age-dependent change in material properties plays a greater role than anatomical changes in driving differences in the deformations. We hope to see increased utilization of these group-average models in both research and clinical applications.

biophysics↗

Characterization of mechanical tissue properties in post-mortem human brain using magnetic resonance elastography

Traumatic brain injury (TBI) is a serious health condition that can cause neurological dysfunction to varying degrees depending on the nature of the mechanical insult. In biomechanical studies of TBI under high loading conditions, post-mortem human subjects (PMHS) are often used since ethical concerns prohibit such experiments in living human subjects. Because PMHS brains undergo significant changes following death, it is important to understand the relationship between the mechanical properties of PMHS brain tissue and living tissue. In this study, we performed magnetic resonance elastography (MRE) on three PMHS specimens to estimate the material properties of the cadaveric brain, namely the storage modulus and the loss modulus, as well as the resulting shear stiffness and damping ratio. We also performed longitudinal MRE scans on one of the PMHS over the span of two months to investigate the evolution of tissue properties with post-mortem degradation. In comparison to in vivo subjects of age range 70-75 years, a substantially higher stiffness (mean: 5.96kPa) and lower damping ratio (mean: 0.09) were found in PMHS models. This study also revealed an initial increase in shear stiffness up to the seventh day post-mortem, followed by a steady decrease by the fifty-eighth day. However, the damping ratio displayed an opposite trend to that of shear stiffness. These changes were heterogeneous across brain regions. The collected measurements and analysis elucidate the changes in mechanical properties in post-mortem subjects, and can be used to build and validate computational models of TBI.

neuroscience↗

Mechanical Properties of the Developing Brain in a Model of Fetal Alcohol Spectrum Disorders and Relationships to Perineuronal Net Integrity

Neuroimaging is a useful tool for examining altered neurodevelopmental trajectories in fetal alcohol spectrum disorders (FASD). FASD affects 1 in 20 infants in the United States with higher prevalence in specific regions across the globe. Advanced neuroimaging methods, such as volumetric morphometry and diffusion-weighted imaging, are critical for determining the effectiveness of interventions that support neurodevelopment in FASD. In this study, we introduce the use of magnetic resonance elastography (MRE), a cutting-edge neuroimaging technique used to measure the mechanical properties of brain tissue, to assess the impact of alcohol exposure and combined exercise and environmental complexity intervention on neurodevelopment in a rat model of FASD. Our results indicate that brain stiffness is reduced in juvenile alcohol-exposed rats which is recovered to baseline by adulthood, and damping ratio increases in all rats with age. Additionally, we quantified cortical perineuronal net (PNN) density which follows similar trends to shear stiffness and damping ratio, suggesting MRE may be an effective method for noninvasively monitoring FASD progression related to extracellular matrix integrity.

neuroscience↗

Mechanical Properties of White Matter Tracts in Aging Assessed via Anisotropic MR Elastography

Magnetic resonance elastography (MRE) is a promising neuroimaging technique to probe tissue microstructure, which has revealed widespread softening with loss of structural integrity in the aging brain. Traditional MRE approaches assume mechanical isotropy. However, white matter is known to be anisotropic from aligned, myelinated axonal bundles, which can lead to uncertainty in mechanical property estimates in these areas when using isotropic MRE. Recent advances in anisotropic MRE now allow for estimation of shear and tensile anisotropy, along with substrate shear modulus, in white matter tracts. The objective of this study was to investigate age-related differences in anisotropic mechanical properties in human brain white matter tracts for the first time. Anisotropic mechanical properties in all tracts were found to be significantly lower in older adults compared to young adults, with average property differences ranging between 0.028-0.107 for shear anisotropy and between 0.139-0.347 for tensile anisotropy. Stiffness perpendicular to the axonal fiber direction was also significantly lower in older age, but only in certain tracts. When compared with fractional anisotropy measures from diffusion tensor imaging, we found that anisotropic MRE measures provided additional, complementary information in describing differences between the white matter integrity of young and older populations. Anisotropic MRE provides a new tool for studying white matter structural integrity in aging and neurodegeneration.

neuroscience↗

Monitoring lasting changes to brain tissue integrity through mechanical properties following adolescent exercise intervention in a rat model of Fetal Alcohol Spectrum Disorders

BackgroundFetal Alcohol Spectrum Disorders (FASD) encompass a group of highly prevalent conditions resulting from prenatal alcohol exposure. Alcohol exposure during the third trimester of pregnancy overlapping with the brain growth spurt is detrimental to white matter growth and myelination, particularly in the corpus callosum, ultimately affecting tissue integrity in adolescence. Traditional neuroimaging techniques have been essential for assessing neurodevelopment in affected youth; however, these methods are limited in their capacity to track subtle microstructural alterations to white matter, thus restricting their effectiveness in monitoring therapeutic intervention. In this preliminary study we use a highly sensitive and clinically translatable Magnetic Resonance Elastography (MRE) protocol for assessing brain tissue microstructure through its mechanical properties following an exercise intervention in a rat model of FASD. MethodsRat pups were divided into two groups: alcohol-exposed (AE) pups which received alcohol in milk substitute (5.25 g/kg/day) via intragastric intubation on postnatal days (PD) four through nine during the rat brain growth spurt (Dobbing and Sands, 1979), or sham-intubated (SI) controls. In adolescence, on PD 30, half AE and SI rats were randomly assigned to either a modified home cage with free access to a running wheel or to a new home cage for 12 days (Gursky and Klintsova, 2017). Previous studies conducted in the lab have shown that 12 days of voluntary exercise intervention in adolescence immediately ameliorated callosal myelination in AE rats (Milbocker et al., 2022, 2023). MRE was used to measure longitudinal changes to mechanical properties of the whole brain and the corpus callosum at intervention termination and one-month post-intervention. Histological quantification of precursor and myelinating oligoglia in corpus callosum was performed one-month post-intervention. ResultsPrior to intervention, AE rats had lower forebrain stiffness in adolescence compared to SI controls (p = 0.02). Exercise intervention immediately mitigated this effect in AE rats, resulting in higher forebrain stiffness post-intervention in adolescence. Similarly, we discovered that forebrain damping ratio was lowest in AE rats in adolescence (p < 0.01), irrespective of intervention exposure. One-month post-intervention in adulthood, AE and SI rats exhibited comparable forebrain stiffness and damping ratio (p > 0.05). Taken together, these MRE data suggest that adolescent exercise intervention supports neurodevelopmental "catch-up" in AE rats. Analysis of the stiffness and damping ratio of the body of corpus callosum revealed that these measures increased with age. Finally, histological quantification of myelinating oligodendrocytes one-month post-intervention revealed a negative rebound effect of exercise cessation on the total estimate of these cells in the body of corpus callosum, irrespective of treatment group which was not convergent with noninvasive MRE measures. ConclusionsThis is the first application of MRE to measure changes in brain mechanical properties in a rodent model of FASD. MRE successfully captured alcohol-related changes to forebrain stiffness and damping ratio in adolescence. These preliminary findings expand upon results from previous studies which used traditional diffusion neuroimaging to identify structural changes to the adolescent brain in rodent models of FASD (Milbocker et al., 2022; Newville et al., 2017). Additionally, in vivo MRE identified an exercise-related alteration to forebrain stiffness that occurred in adolescence, immediately post-intervention.

bioengineering↗

Mechanical Property Based Brain Age Prediction using Convolutional Neural Networks

Brain age is a quantitative estimate to explain an individuals structural and functional brain measurements relative to the overall population and is particularly valuable in describing differences related to developmental or neurodegenerative pathology. Accurately inferring brain age from brain imaging data requires sophisticated models that capture the underlying age-related brain changes. Magnetic resonance elastography (MRE) is a phase contrast MRI technology that uses external palpations to measure brain mechanical properties. Mechanical property measures of viscoelastic shear stiffness and damping ratio have been found to change across the entire life span and to reflect brain health due to neurodegenerative diseases and even individual differences in cognitive function. Here we develop and train a multi-modal 3D convolutional neural network (CNN) to model the relationship between age and whole brain mechanical properties. After training, the network maps the measurements and other inputs to a brain age prediction. We found high performance using the 3D maps of various mechanical properties to predict brain age. Stiffness maps alone were able to predict ages of the test group subjects with a mean absolute error (MAE) of 3.76 years, which is comparable to single inputs of damping ratio (MAE: 3.82) and outperforms single input of volume (MAE: 4.60). Combining stiffness and volume in a multimodal approach performed the best, with an MAE of 3.60 years, whereas including damping ratio worsened model performance. Our results reflect previous MRE literature that had demonstrated that stiffness is more strongly related to chronological age than damping ratio. This machine learning model provides the first prediction of brain age from brain biomechanical data--an advancement towards sensitively describing brain integrity differences in individuals with neuropathology.

bioengineering↗

Development and Validation of Subject-Specific 3D Human Head Models Based on a Nonlinear Visco-Hyperelastic Constitutive Framework

Computational models of the human head are promising tools for the study and prediction of traumatic brain injuries (TBIs). Most available head models are developed using inputs (i.e., head geometry, material properties, and boundary conditions) derived from ex-vivo experiments on cadavers or animals and employ linear viscoelasticity (LVE)-based constitutive models, which leads to high uncertainty and poor accuracy in capturing the nonlinear response of brain tissue under impulsive loading conditions. To resolve these issues, a framework for the development of fully subject-specific 3D human head models is proposed, in which model inputs are derived from the same living human subject using a comprehensive in-vivo brain imaging protocol, and the viscous dissipation-based visco-hyperelastic constitutive modeling framework is employed. Specifically, brain tissue material properties are derived from in-vivo magnetic resonance elastography (MRE), and full-field strain-response of brain under rapid rotational acceleration is obtained from tagged MRI, which is used for model validation. The constitutive model comprises the Ogden hyperelastic strain energy density and the Upadhyay-Subhash-Spearot viscous dissipation potential. The simulated strain-response is compared with experimental data and with predictions from subject-specific models employing two commonly used LVE-based constitutive models, using a rigorous validation procedure that evaluates agreement in spatial strain distribution, temporal strain evolution, and differences in maximum values of peak and average strain. Results show that the head model developed in this work reasonably captures 3D brain dynamics, and when compared to LVE-based models, provides improvements in the prediction of peak strains and temporal strain evolution.

bioengineering↗

MM-MRE: a new technique to quantify individual muscle forces during isometric tasks of the wrist using MR elastography

Non-invasive in-vivo measurement of individual muscle force is limited by the infeasibility of placing force sensing elements in series with the musculo-tendon structures. At the same time, estimating muscle forces using EMG measurements is prone to inaccuracies, as EMG is not always measurable for the complete set of muscles acting around the joints of interest. While new methods based on shear wave elastography have been recently proposed to directly characterize muscle mechanics, they can only be used to measure muscle forces in a limited set of superficial muscles. As such, they are not suitable to study the neuromuscular control of movements that require coordinated action of multiple muscles.\n\nIn this work, we present multi-muscle magnetic resonance elastography (MM-MRE), a new technique capable of quantifying individual muscle force from the complete set of muscles in the forearm, thus enabling the study of the neuromuscular control of wrist movements. MM-MRE integrates measurements of joint torque provided by an MRI-compatible instrumented handle with muscle-specific measurements of shear wave speed obtained via MRE to quantify individual muscle force using model-based estimator.\n\nA single-subject pilot experiment demonstrates the possibility of obtaining measurements from individual muscles and establishes that MM-MRE has sufficient sensitivity to detect changes in muscle mechanics following the application of isometric joint torque with self-selected intensity.

bioengineering↗

The Anorexia Nervosa Genetics Initiative: Overview and Methods

BackgroundGenetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13000 individuals with AN as well as ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.\n\nMethodsANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.\n\nResultsBlood samples and clinical information were collected from 13,364 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.\n\nConclusionsOur multipronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.gov NCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.

genetics↗