Ronald J. Beyers’s research while affiliated with Auburn University and other places

Background Magnetic resonance imaging (MRI) is increasingly used to estimate the geometric dimensions of lower lumbar vertebrae. While MRI-based measurements have demonstrated good reliability with interclass correlation coefficients (ICCs) of 0.80 or higher, many evaluations focus solely on the comparison of identical MRI images. This approach primarily reflects analyst dexterity and does not assess the reliability of the entire process, including imaging and image selection. Objective To evaluate the inter- and intra-rater reliability of the entire process of using MRI to measure biomechanically relevant lumbar spinal characteristics, incorporating imaging, image selection, and analysis. Methods: A dataset of 144 low-back MRI scans was analyzed. Reliability assessments were performed under different conditions: (1) identical scans rated by the same analyst at different times (intra-rater reliability) and (2) distinct scans of the same subject obtained by different MRI operators and analyzed by different analysts (inter-rater reliability). Mean absolute differences in measurements were calculated, and sources of variability, such as breathing artifacts, were noted. Results Larger discrepancies were observed when comparing distinct scans analyzed by different MRI operators and analysts. In the “worst-case” scenario, where both the MRI operator and analyst differed, a 4.05% mean absolute difference was noted for anterior endplate measurements. This was higher than the 2.76% difference observed when analysts re-rated their own scans after one month. Despite these discrepancies, the variability in measurements was relatively low and primarily attributed to factors like breathing artifacts. Conclusion The process of using MRI to derive biomechanical measures, particularly for bony structures, demonstrates robust reliability. Variability in measurements is minimal even under challenging conditions, supporting the use of MRI for biomechanical assessments.

This study introduces a biocompatible, stimuli-responsive imaging and therapeutic delivery system using ultrasmall iron oxide nanoparticles (USPIONs) encapsulated within hyaluronic acid-b-poly(lactic acid) (HA-PLA) polymersome membrane and a model protein bovine...

This study introduces a biocompatible, stimuli-responsive imaging and therapeutic delivery system using ultrasmall iron oxide nanoparticles (USPIONs) encapsulated within hyaluronic acid-b-poly(lactic acid) (HA-PLA) polymersome membrane and a model protein bovine serum albumin in the core. These multilamellar vesicles exhibit enhanced T2-weighted MRI contrast, achieving a relaxivity 3-fold higher than existing agents. The polymersomes demonstrate acid- and enzyme-triggered degradation, enabling controlled release and measurable contrast changes in pathological environments. Preliminary in vivo and postmortem studies confirm their strong imaging performance, high biocompatibility, and targeted response to enzymatic, acidic microenvironments, paving the way for theranostic applications in disease diagnosis and treatment monitoring.

Simple Summary The expense associated with training detection and service dogs is significant. By employing resting-state functional resonance imaging technique, a non-invasive method capable of probing brain function, we can identify the critical brain regions linked to selecting dogs inclined towards successful training. These biomarkers identified before commencement of training predict successful trainability and hence reduce training costs by obviating the need to invest in dogs that are unlikely to be successful. Furthermore, our research extends to elucidating the identified brain regions in dogs that exhibit homologous functions to those found in the human brain, offering valuable insights into the evolutionary parallels between humans and our closest animal companions. Abstract Functional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting-state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score capturing their hunting, retrieving, and environmental soundness. Functional scans and behavioral measures were acquired at three different time points across detector dog training. The first time point (TP1) was prior to the dogs entering formal working detector dog training. The second time point (TP2) was soon after formal detector dog training. The third time point (TP3) was three months’ post detector dog training while the dogs were engaged in a program of maintenance training for detection work. We hypothesized that the correlation between resting-state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2) and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting-state FC features that can predict the success of training, dogs at TP1 were divided into a successful group and a non-successful group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in successful detector dogs compared to failures and whose connectivity strength at the first time point predicted whether a given dog was eventually successful in becoming a detector dog. A second ontologically based flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior over the training program. Comparing dog and human brains, the functional connectivity between the brain stem and the frontal cortex in dogs corresponded to that between the locus coeruleus and left middle frontal gyrus in humans, suggestive of a shared mechanism for learning and retrieval of odors. Overall, the findings point toward the influence of phylogeny and ontogeny in dogs producing two dissociable functional neural networks.

We examined how set-volume equated resistance training using either the back squat (SQ) or hip thrust (HT) affected hypertrophy and various strength outcomes. Untrained college-aged participants were randomized into HT (n = 18) or SQ (n = 16) groups. Surface electromyograms (sEMG) from the right gluteus maximus and medius muscles were obtained during the first training session. Participants completed 9 weeks of supervised training (15–17 sessions), before and after which gluteus and leg muscle cross-sectional area (mCSA) was assessed via magnetic resonance imaging. Strength was also assessed prior to and after the training intervention via three-repetition maximum (3RM) testing and an isometric wall push test. Gluteus mCSA increases were similar across both groups. Specifically, estimates [(−) favors HT (+) favors SQ] modestly favored the HT versus SQ for lower [effect ±SE, −1.6 ± 2.1 cm²; CI95% (−6.1, 2.0)], mid [−0.5 ± 1.7 cm²; CI95% (−4.0, 2.6)], and upper [−0.5 ± 2.6 cm²; CI95% (−5.8, 4.1)] gluteal mCSAs but with appreciable variance. Gluteus medius + minimus [−1.8 ± 1.5 cm²; CI95% (−4.6, 1.4)] and hamstrings [0.1 ± 0.6 cm²; CI95% (−0.9, 1.4)] mCSA demonstrated little to no growth with small differences between groups. mCSA changes were greater in SQ for the quadriceps [3.6 ± 1.5 cm²; CI95% (0.7, 6.4)] and adductors [2.5 ± 0.7 cm²; CI95% (1.2, 3.9)]. Squat 3RM increases favored SQ [14 ± 2 kg; CI95% (9, 18),] and hip thrust 3RM favored HT [−26 ± 5 kg; CI95% (−34, −16)]. 3RM deadlift [0 ± 2 kg; CI95% (−4, 3)] and wall push strength [−7 ± 12N; CI95% (−32, 17)] similarly improved. All measured gluteal sites showed greater mean sEMG amplitudes during the first bout hip thrust versus squat set, but this did not consistently predict gluteal hypertrophy outcomes. Squat and hip thrust training elicited similar gluteal hypertrophy, greater thigh hypertrophy in SQ, strength increases that favored exercise allocation, and similar deadlift and wall push strength increases.

Purpose: We examined how set-volume equated resistance training using either the back squat (SQ) or hip thrust (HT) affected hypertrophy and various strength outcomes. Methods: Untrained college-aged participants were randomized into HT (n=18) or SQ (n=16) groups. Surface electromyograms (sEMG) from the right gluteus maximus and medius muscles were obtained during the first training session. Participants completed nine weeks of supervised training (15-17 sessions), before and after which we assessed muscle cross-sectional area (mCSA) via magnetic resonance imaging and strength via three-repetition maximum (3RM) testing and an isometric wall push test. Results: Glutei mCSA growth was similar across both groups. Estimates [(-) favors HT; (+) favors SQ] modestly favored the HT compared to SQ for lower [effect +/- SE, -1.6 +/- 2.1 cm2], mid [-0.5 +/- 1.7 cm2], and upper [-0.5 +/- 2.6 cm2], but with appreciable variance. Gluteus medius+minimus [-1.8 +/- 1.5 cm2] and hamstrings [0.1 +/- 0.6 cm2] mCSA demonstrated little to no growth with small differences between groups. Thigh mCSA changes were greater in SQ for the quadriceps [3.6 +/- 1.5 cm2] and adductors [2.5 +/- 0.7 cm2]. Squat 3RM increases favored SQ [14 +/- 2.5 kg] and hip thrust 3RM favored HT [-26 +/- 5 kg]. 3RM deadlift [0 +/- 2 kg] and wall push strength [-7 +/- 13 N] similarly improved. All measured gluteal sites showed greater mean sEMG amplitudes during the first bout hip thrust versus squat set, but this did not consistently predict gluteal hypertrophy outcomes. Conclusion: Nine weeks of squat versus hip thrust training elicited similar gluteal hypertrophy, greater thigh hypertrophy in SQ, strength increases that favored exercise allocation, and similar strength transfers to the deadlift and wall push.

Mild cognitive impairment (MCI) and early Alzheimer’s disease (AD) are characterized by blood–brain barrier (BBB) breakdown leading to abnormal BBB permeability ahead of brain atrophy or dementia. Previous findings in AD mouse models have reported the beneficial effect of extra-virgin olive oil (EVOO) against AD, which improved BBB and memory functions and reduced brain amyloid-β (Aβ) and related pathology. This work aimed to translate these preclinical findings to humans in individuals with MCI. We examined the effect of daily consumption of refined olive oil (ROO) and EVOO for 6 months in MCI subjects on BBB permeability (assessed by contrast-enhanced MRI), and brain function (assessed using functional-MRI) as the primary outcomes. Cognitive function and AD blood biomarkers were also assessed as the secondary outcomes. Twenty-six participants with MCI were randomized with 25 participants completed the study. EVOO significantly improved clinical dementia rating (CDR) and behavioral scores. EVOO also reduced BBB permeability and enhanced functional connectivity. While ROO consumption did not alter BBB permeability or brain connectivity, it improved CDR scores and increased functional brain activation to a memory task in cortical regions involved in perception and cognition. Moreover, EVOO and ROO significantly reduced blood Aβ42/Aβ40 and p-tau/t-tau ratios, suggesting that both altered the processing and clearance of Aβ. In conclusion, EVOO and ROO improved CDR and behavioral scores; only EVOO enhanced brain connectivity and reduced BBB permeability, suggesting EVOO biophenols contributed to such an effect. This proof-of-concept study justifies further clinical trials to assess olive oil’s protective effects against AD and its potential role in preventing MCI conversion to AD and related dementias.

A highly water‐ and air‐stable Fe(II) complex with the quinol‐containing macrocyclic ligand H4qp4 reacts with H2O2 to yield Fe(III) complexes with less highly chelating forms of the ligand that have either one or two para‐quinones. The reaction increases the T1‐weighted relaxivity over four‐fold, enabling the complex to detect H2O2 using clinical MRI technology. The iron‐containing sensor differs from its recently characterized manganese analog, which also detects H2O2, in that it is the oxidation of the metal center, rather than the ligand, that primarily enhances the relaxivity.

We evaluated the effects of higher-load (HL) versus (lower-load) higher-volume (HV) resistance training on skeletal muscle hypertrophy, strength, and muscle-level molecular adaptations. Trained men (n = 15, age: 23 ± 3 years; training experience: 7 ± 3 years) performed unilateral lower-body training for 6 weeks (3× weekly), where single legs were randomly assigned to HV and HL paradigms. Vastus lateralis (VL) biopsies were obtained prior to study initiation (PRE) as well as 3 days (POST) and 10 days following the last training bout (POSTPR). Body composition and strength tests were performed at each testing session, and biochemical assays were performed on muscle tissue after study completion. Two-way within-subject repeated measures ANOVAs were performed on most dependent variables, and tracer data were compared using dependent samples t-tests. A significant interaction existed for VL muscle cross-sectional area (assessed via magnetic resonance imaging; interaction p = 0.046), where HV increased this metric from PRE to POST (+3.2%, p = 0.018) whereas HL training did not (−0.1%, p = 0.475). Additionally, HL increased leg extensor strength more so than HV training (interaction p = 0.032; HV < HL at POST and POSTPR, p < 0.025 for each). Six-week integrated non-myofibrillar protein synthesis (iNon-MyoPS) rates were also higher in the HV versus HL condition, while no difference between conditions existed for iMyoPS rates. No interactions existed for other strength, VL morphology variables, or the relative abundances of major muscle proteins. Compared to HL training, 6 weeks of HV training in previously trained men optimizes VL hypertrophy in lieu of enhanced iNon-MyoPS rates, and this warrants future research.