NMR in Biomedicine

Background: Acute phase response is an early immunometabolic response to brain injuries, primarily coordinated by the liver via the activation of acute phase proteins. These immune responses can be both beneficial, promoting tissue repair, and detrimental, exacerbating neurological deficits, if not properly controlled. Despite the central role of the liver in immunometabolism, how hepatic metabolism dynamically adapts to traumatic brain injury remains under explored, primarily due to limited liver-specific modalities that can assess metabolic pathways in vivo. 13C MRI utilizing hyperpolarized 13C-pyruvate can assess key regulatory enzyme activities in hepatic metabolism. Methods: Rats with controlled cortical impact were studied in vivo using hyperpolarized [1-13C]pyruvate and [2-13C]pyruvate under fed and fasted conditions 3-4 days after injury. Hyperpolarized 13C products, including [13C]bicarbonate from [1-13C]pyruvate and [5-13C]glutamate, [1-13C]acetyl-L-carnitine, and [2-13C]phosphoenolpyruvate from [2-13C]pyruvate, were evaluated to assess mitochondrial and gluconeogenic metabolism. In parallel, liver tissues were collected following [U-13C3]pyruvate injection for NMR isotopomer analysis of phosphoenolpyruvate, glucose, and glutamate. Results: While no metabolic differences were detected under fed condition, [13C]bicarbonate and [2-13C]phosphoenolpyruvate increased after brain injury under fasted condition, indicating an upregulation of the hepatic gluconeogenic pathway after injury. 13C NMR of liver tissue extracts from injured rats showed an elevated [2,3-13C2]glutamate-to-[4,5-13C2]glutamate ratio and increased 13C-labeling in phosphoenolpyruvate than controls, confirming enhanced hepatic gluconeogenic pathway. Conclusion: This study demonstrates that hepatic acute phase response to brain injuries can be monitored in vivo by hyperpolarized pyruvate, which may be further utilized for longitudinal immunometabolic evaluation of the liver during pathogenesis and therapeutic interventions.

Diffusion-weighted MRI, beyond the commonly used diffusion tensor framework, offers a unique window into tissue microstructure in vivo, yet its clinical adoption has remained limited. Major barriers include the complexity of diffusion MRI sequence design, lengthy acquisition protocols, and the challenges associated with robust estimation of high-dimensional microstructural model parameters. Here, we address these limitations by combining optimised diffusion encoding with state-of-the-art simulation-based inference, establishing a clinically feasible framework for multi-compartment diffusion modelling. We validate the approach through i) in-depth in silico experiments and ii) in vivo studies made up of both human and rodent data. The resulting microstructural metrics are robust, reproducible across healthy individuals and show significant spatial associations with brain-wide expression patterns of cell-specific genes. Requiring less than 10 minutes of acquisition time, this framework substantially lowers the barriers to advanced microstructural imaging, a prerequisite step toward its eventual evaluation for the diagnosis, stratification, and monitoring of brain disorders.

Purpose: The primary objective of the Stanford Knee Osteoarthritis PET/MRI Evaluation (SKOPE) study is to develop and evaluate a multimodal, dynamic [18F]NaF PET-MRI framework for characterizing whole-joint physiology and its relationship to osteoarthritis (OA) risk, pain, and disease progression. Specifically, we aim to integrate dynamic PET with quantitative and anatomical MRI, to characterize structural, compositional, and metabolic features across the knee and surrounding musculoskeletal system, evaluate acute tissue responses to exercise, and identify imaging biomarkers associated with OA risk, pain, and disease progression. Methods: The SKOPE study includes multimodal PET-MRI of the knee and surrounding musculoskeletal tissues, with imaging of the knee, tibia, ankle, thigh, hip, pelvis, and lumbosacral spine. Dynamic [18F]NaF PET is combined with conventional anatomical MRI and quantitative MRI techniques, including quantitative double-echo steady-state (qDESS) T2 mapping of cartilage, Dixon fat-fraction imaging, ultrashort echo time (UTE) T2* mapping of short-T2 tissues, UTE imaging of tibial bone, and zero echo time (ZTE) imaging for bone morphology and pseudo-CT generation. Additional MRI sequences characterize muscle composition, bone and joint anatomy, intervertebral discs, and regional vascular anatomy. Selected scans are acquired before and after a standardized exercise protocol to assess the acute physiological response of the joint. Automated segmentation is used to generate subject-specific masks of muscles, bones, vertebrae, and intervertebral discs. A subset of the MRI protocol is repeated at 1- and 2-year follow-up to assess longitudinal changes. Expected Impact: By combining dynamic bone metabolic imaging with quantitative measures of cartilage, menisci, muscle, bone, fat, vascular structures, and the spine and hip, the SKOPE protocol provides a whole-joint and multijoint framework for studying the structural, metabolic, and physiological processes associated with OA and pain. Exercise and longitudinal imaging further enable assessment of acute tissue responses and changes over time, supporting the development of quantitative imaging biomarkers for OA risk, pain, and disease progression.

Dynamic positron emission tomography (PET) with long axial field-of-view (LAFOV) scanners enables multi-organ imaging and kinetic quantification beyond static (late-phase) imaging; however, the long times typically required for dynamic acquisitions remain clinically impractical. This study evaluates a deep learning (DL) framework to enable abbreviated dynamic PET acquisitions, comparing single-time-window (STW, early dynamic data only) and dual-time-window (DTW, early dynamic data plus a late 5-min static frame) protocols with early dynamic scan durations of 5-30 min and dose levels ranging from 360 MBq to 18 MBq. Seventeen 60-min dynamic [18F]FDG datasets were first motion-corrected using a staggered FALCON pipeline and then used to train and test a spatiotemporal DL model for autoregressive frame prediction. Performance was assessed across the full quantitative workflow, from DL-predicted frames and time-activity curves to organ-based kinetic modeling and voxel-wise parametric imaging in multiple tissues and two patient cohorts. DTW protocols consistently outperformed STW, better preserving late-phase kinetics. For a 15-min early dynamic scan, adding a late 5-min scan reduced mean absolute Ki difference from 23% (STW) to 17% (DTW) in the liver and from 26% to 15% in the thalamus. DTW + DL further reduced errors to [≤]10% in the liver, thalamus, and breast lesion, and 16% in muscle. Our recommended protocol, 15-min early dynamic scan plus a 5-min late scan with DL, remained robust to up to a 5-fold dose reduction (~74 MBq). Overall, these findings support DL-enabled abbreviated, low-dose dynamic LAFOV PET as a clinically feasible approach for accurate kinetic quantification

Muscle architecture shapes muscle function and changes with age, growth, training and disease, yet quantifying three-dimensional (3D) muscle architecture in vivo remains challenging. We introduce a hybrid fascicle tractography approach for freehand 3D ultrasound data that accurately reconstructs 3D muscle fascicles with respect to an objective, anatomically relevant coordinate system defined by the muscle's central aponeurosis. The hybrid approach combines Hessian-based fascicle detection with wavelet-based refinement to generate volumetric fascicle orientations. In a synthetic dataset with known ground truth, fascicle orientations and lengths were estimated with errors of [≤]2{degrees} and ~1.5%, respectively. In vivo, the approach detected physiologically plausible fascicle lengthening in the human tibialis anterior following a passive plantar flexion rotation, whereas diffusion tensor imaging of the same muscle did not. The proposed method enables anatomically relevant, objective and non-invasive quantification of 3D muscle architecture in vivo, providing a practical framework for applications in clinical and applied muscle physiology.

Alzheimer's disease (AD) pathology involves amyloid deposition, reactive gliosis, and localized tissue alterations that coexist within the same brain regions, creating heterogeneous microstructural environments within individual imaging voxels. Conventional diffusion MRI averages these environments into aggregate measures, potentially obscuring their distinct contributions. Frequency-dependent multidimensional MRI ({omega}MD-MRI) resolves distributions of water components with different diffusion length scales, anisotropies, and relaxation properties, providing sensitivity to microstructural restriction, heterogeneity, and shape-size correlations within a voxel. Whether these measurements reveal microstructural complexity associated with AD pathology remains unclear. Here, we performed {omega}MD-MRI on ex vivo brain specimens from approximately 8-month-old 5xFAD and wild-type mice and interpreted the imaging findings alongside complementary histology. {omega}MD-MRI revealed widespread but spatially nonuniform differences between 5xFAD and wild-type brains. Measurements sensitive to microstructural restriction, heterogeneity, and shape-size correlations consistently indicated greater microstructural heterogeneity in 5xFAD brains, with the most prominent differences in the hippocampal formation and major cerebral white matter tracts. Complementary qualitative histology demonstrated extensive amyloid deposition and glial activation in affected regions, while overall cytoarchitecture and myelin organization remained largely preserved. Thus, the {omega}MD-MRI abnormalities occurred in tissue characterized by multiple coexisting pathological and relatively preserved microstructural environments rather than widespread structural degeneration. These findings demonstrate that {omega}MD-MRI can reveal the spatial and microstructural heterogeneity associated with amyloid pathology and provide a more comprehensive characterization of AD-related tissue alterations.

Rationale: Neuroblastoma is a devastating pediatric malignancy, for which surgical resection is a key factor in long-term survival. However, there are significant challenges in its resection, particularly in high-risk disease, as neuroblastoma encases surrounding critical structures, is often difficult to distinguish from desmoplastic or scar tissue, and can carry occult deposits of disease not readily identified on preoperative imaging or intraoperative visualization. Building on the principles of fluorescent and radio-guided surgery, in combination with the known overexpression of GD2 in neuroblastoma, we sought to develop and optimize 111In-Dinutuximab-IRDye800, a dual-modality GD2-targeted intraoperative molecular imaging agent, for use in pediatric neuroblastoma to help enhance patient safety while facilitating a more complete resection. Methods: Dinutuximab was conjugated to IRDye800 and DTPA, then radiolabeled with Indium-111 to yield 111In-Dinutuximab-IRDye800. Optimization occurred through ELISA assay to assess binding affinity, fluorescence intensity analysis to determine the optimal fluorescent degree of labeling, and phototoxicity testing through flow cytometry. Rodent models of neuroblastoma were then generated through injection of SK-N-BE(2) human neuroblastoma cells into the left adrenal glands of nude mice or RNU rats. A series of fluorescent and gamma biodistributions was performed, varying the dose, timing, and specific activity of the tracer. Tumor and organ uptake of the tracer was compared with one- or two-way ANOVA as appropriate, with Sidaks multiple comparison test to compare tumor uptake to individual organs. Once optimization was complete, a clinically significant events study modeled after human clinical trials was performed to evaluate the in vivo capabilities of 111In-Dinutuximab-IRDye800. Results: Increased ratios of IRDye800 per antibody led to decreased binding affinity for GD2 and was associated with formulation instability without significant return on fluorescence intensity. Specific activity of the tracer was not found to impact overall biodistribution of the tracer. A 45-50 microgram dose of 111In-Dinutuximab-IRDye800 with ratios around 1 DTPA and 1-1.5 IRDye800 per antibody imaged 4 days after tracer administration was found to be the optimal combination that maximized detectable tumor-specific signal. In the clinically significant events study mirroring human IMI clinical trials, fluorescent guidance identified additional malignant lesions not originally detected under white light in 64% of rodents. Conclusions: 111In-Dinutuximab-IRDye800 is a dual-modality GD2-targeted intraoperative imaging agent that is well-poised for clinical translation. As it preserves tumor specificity, yields clinically meaningful radiofluorescent signal, and is well-tolerated without adverse events after optimization was completed, it carries the potential to positively impact the safety and completeness of neuroblastoma resection.

Neutron scattering is a powerful technique to investigate atomic structures and molecular dynamics of proteins at the nano-scale. When it comes to dynamics, incoherent and coherent scattering respectively provide information on the single and collective dynamics of nuclei. In proteins, hydrogen has the highest incoherent cross-section, and it is common practice to overlook the contribution of coherent terms stemming from all nuclei. However, the fast collective dynamics of heavier nuclei could also be studied if coherent scattering and incoherent scattering were experimentally separated. The recent advent of polarized neutron spectroscopy with sufficient flux and energy resolution has made it possible, and opens new perspectives to investigate the relative importance of coherent scattering and the information it provides on biological samples. The present study reports on the use of polarized quasi-elastic neutron scattering (QENS) and the application of a minimalistic model adapted to both individual and collective dynamics. Using a perdeuterated green fluorescent protein as a model globular protein, the study provides an interpretation of the dynamical parameters obtained with QENS, and a comparative study of the Elastic Coherent and Incoherent Scattering Factor. Based on both experiments and calculations, we discuss the relative importance of distinct and self components of coherent scattering, which is often wrongly assumed to be representative of collective dynamics only. The results highlight the current impediments rendering complicated a straightforward analysis of fast collective dynamics in hydrated protein samples.

Study design Retrospective cohort study. Objectives To correlate Hounsfield unit (HU) values, using elliptical regions of interest (ROI), that can be easily defined in routine clinical practice with magnetic resonance imaging (MRI) T2-hyperintense area fraction, as a surrogate for paraspinal muscle fat infiltration and to establish specific HU screening thresholds that may be applied with standard picture archiving and communication system (PACS). Methods We included 136 patients (71 men; 61.0 {+/-} 15.4 years) who underwent preoperative computed tomography (CT) and MRI within an 8-week period. Elliptical ROI HU values were measured at L2/3 and L4/5 for erector spinae, multifidus, and psoas major. MRI T2-hyperintense area fraction (Otsu thresholding) served as the fat infiltration reference. Linear mixed-effects (LME) models were used to assess the HU-T2 association and level-specific receiver operating characteristic (ROC) analyses (lower HU value side; n=136 per muscle-level) to identify thresholds for [≥]30% and [≥]50% infiltration criteria. Results Intraclass coefficients = 0.709 (HU) and 0.857 (T2 fraction); Goutallier weighted kappa = 0.579. In the overall LME, {beta} was -0.880 HU per 1% T2-fraction increase (95% confidence interval -0.935 to -0.825; marginal R2 =0.502); the association was steeper in multifidus ({beta} = -1.020) than in erector spinae ({beta} = -0.753). Psoas major (R = -0.226) was excluded from ROC analyses. Difference between L2/3 and L4/5 HU cutoffs was ~20 HU. The [≥]50% criterion revealed higher discrimination. Conclusions Elliptical ROI-based HU measurements may reliably screen paraspinal muscle fat infiltration in erector spinae and multifidus using standard PACS. Specific thresholds may allow practical preoperative evaluation without additional costs or radiation.

Background: Hippocampal sclerosis (HS) is a common cause of drug-resistant focal epilepsy (DRFE) and amenable to neurosurgical treatment. Detection relies on MRI but can be challenging. 7 Tesla (T) ultra-high field MRI and automated MRI post-processing tools have independently been shown to improve radiological diagnosis of HS. However, combining these approaches remains underexplored. This study evaluated whether AID-HS, a tool for HS detection developed using 3T MRI, generalises to 7T MRI data. Methods: We collated a dataset of paired 3T and 7T T1-weighted MRI from four epilepsy centres, including 23 patients with HS, 39 healthy controls, and 23 individuals with focal cortical dysplasia as disease controls. Histopathology served as the gold standard for defining HS where available (n=7), otherwise radiological findings (n=16). AID-HS was applied to images acquired at both field strengths, and sensitivity and specificity for detection and lateralisation of HS were compared. Additionally, agreement of hippocampal features across 3T and 7T was evaluated. Results: We found no evidence of a difference in performance of AID-HS between 3T and 7T. Sensitivity for detection of unilateral HS was 63% (12/19) at 3T and 68% (13/19) at 7T (McNemar's exact test p=1.0). Specificity in controls was 97% (60/62) at 3T and 100% (62/62) at 7T (p=0.5). Bilateral HS was correctly flagged in 3 of 4 cases using feature-based criteria, with high specificity in controls. Quantitative hippocampal features showed moderate to good agreement across field strengths (ICC 0.70 to 0.98), with small differences observed for volume and thickness estimates. Conclusion: AID-HS provides robust detection and lateralisation of HS across multiple 7T MRI centres, highlighting its potential to enhance lesion detection. Future work is needed to investigate whether models trained on 7T data can leverage the improved image quality for further gains in HS detection performance.

Diffusion models achieve high reconstruction quality in low-dose computed tomography (LDCT), but their iterative sampling trajectories impose substantial computational costs. Unlike unconditional generation, paired LDCT reconstruction starts from an image that already contains the anatomy and spatial structure of the standard-dose CT (SDCT) target; reconstruction primarily requires correcting dose-related noise and artifacts. We therefore introduce Residual Endpoint Flow Matching (REFM), an LDCT reconstruction method that learns to transport an LDCT image directly toward its paired SDCT endpoint rather than defining a noise-to-image trajectory. REFM predicts the residual velocity along linear interpolations between both images and supports single-step and multi-step reconstruction using the same trained network. We evaluate five model capacities using 1 to 50 Euler steps against deterministic U-Net and diffusion-based baselines. Across all REFM variants, one-step inference consistently provides the highest reconstruction quality. On the TCIA validation set, REFM Base achieves 50.98 dB PSNR and 0.9865 SSIM at 94.54 fps, compared with 50.92 dB, 0.9847, and 9.26 fps for DDPM-10. REFM Small retains 50.71 dB while increasing throughput to 198.56 fps. Without fine-tuning, REFM Base also matches the 25-step DDPM baseline on the external Mayo Clinic dataset, although DDPM remains stronger on synthetically degraded CRLM images. Thus, our results show that exploiting paired anatomical correspondence enables diffusion-level LDCT reconstruction with a single step reconstruction.

Cross-sectional studies suggest associations between physical exercise and white matter in older adults, but evidence from randomized controlled trials is scarce. Neurite orientation dispersion and density imaging indices are biophysically informed metrics of white matter microstructure. Here, we tested whether a remotely delivered, 8-week multicomponent physical exercise intervention impacts neurite density (NDI) and orientation dispersion (ODI) across major white matter tracts in older adults. This secondary analysis of a randomized controlled trial included participants with available diffusion MRI data (n = 66; age: 66.4 {+/-} 3.6 y; 43 females). Participants were randomized to a multicomponent exercise (PAG, n = 34) or an active control (CON, n = 32) intervention. Intervention effects on NDI/ODI were tested using linear mixed-effects and Bayesian multilevel models adjusted for age and sex. A significant Timepoint x Group interaction was observed for NDI (p = 0.003) but not for ODI (p = 0.785), further confirmed in Bayesian analyses for 22 white matter tracts, indicating a greater increase in NDI in the PAG. The standardized composite VO2max score increased from pre- to post-intervention within the PAG, although the Timepoint x Group interaction was not significant (p = 0.079). Across all participants, pre-to-post changes in mean NDI were positively correlated with changes in VO2max, but this association did not differ between groups. Our results indicate that white matter microstructure remains responsive to short-term, multicomponent physical exercise in older adults.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major cause of chronic liver disease, with weight loss as the pivotal therapeutic strategy. However, the metabolic and molecular adaptations underlying rapid weight loss remain incompletely defined. In this pilot study, women with obesity and MASLD but without diabetes consumed a very low-calorie diet (VLCD) for 8 weeks. Clinical parameters, hepatic steatosis measured by controlled attenuation parameter (CAP), circulating metabolites, and microRNAs (miRs) were assessed before and after the dietary intervention. Integrated correlation and hierarchical clustering analyses were performed to identify molecular networks associated with clinical improvement. VLCD was well tolerated, resulting in significant weight loss (~11%) with ~80% adherence. Significant improvements in metabolic parameters were observed, including fat mass, waist circumference, blood pressure, insulinemia, HOMA-IR, HbA1c, and triglycerides, with unchanged liver enzymes. Hepatic steatosis decreased markedly, as indicated by a reduction in CAP, while stiffness remained unchanged. Metabolomic profiling revealed elevated ketone bodies and broad reductions in amino acid levels, consistent with enhanced fatty acid oxidation and a catabolic metabolic state. Correlation analysis identified distinct metabolite signatures associated with hepatic steatosis, with changes in CAP positively associated with changes in amino acids and inversely associated with changes in ketone bodies and tricarboxylic acid cycle intermediates. Circulating miRs underwent selective rather than global remodeling, with only a limited subset showing strong associations with clinical parameters, including CAP and HOMA-IR. Specifically, VLCD altered the circulating levels of miR-148a-3p, miR-140-3p, miR-10b-5p, and miR-345-5p. Integration of metabolomic and miR datasets identified coordinated metabolite-miR modules involving glucose metabolism, branched-chain amino acid catabolism, mitochondrial metabolism, purine metabolism, microbial metabolites, and cellular redox pathways. These findings demonstrate that improvement in hepatic steatosis during VLCD-induced weight loss is accompanied by coordinated remodeling of circulating metabolite-miR networks. Integrated multi-omics analysis identifies candidate molecular signatures associated with metabolic adaptation and highlights circulating miR-metabolite modules as potential biomarkers of therapeutic response in MASLD.

Objectives: Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability by eliciting motor evoked potential (MEP)s in targeted muscles, with MEP characteristics such as magnitude and latency reflecting the physiological state of the pathways being stimulated. Although numerous studies have examined MEP reliability in upper extremity muscles, less is known about the reliability of this measurement across the lower extremity. We hypothesized that inter-session, test-retest reliability of MEPs recorded simultaneously from multiple lower-limb muscles, from a single TMS location, would differ by muscle, stimulation intensity, and quantification method. Materials and Methods: Ten healthy participants (5 males, 5 females) completed three TMS sessions separated by atleast one week. At each session, the stimulation hotspot was identified using a five-location virtual grid anchored at the vertex, with electromyography (EMG) recorded from all eight muscles of interest at each grid location; the grid location producing the largest and most consistent MEPs in the tibialis anterior (TA), the primary target muscle, was selected as the stimulation site and held constant across all three sessions. MEPs were then recorded bilaterally from the TA, soleus, rectus femoris, and biceps femoris muscles at two stimulation intensities (110% and 120% resting motor threshold (RMT)). MEP size was quantified using mean rectified magnitude and peak-to-peak amplitude, and inter-session reliability was assessed using intraclass correlation coefficients (ICC). Bland-Altman analysis was used to characterize the range of measurement variability across all eight muscles. Results: MEP size differed across sessions, and reliability varied by muscle, intensity, and quantification method. The highest reliability was observed in the right TA, the muscle used to establish the stimulation hotspot, using mean rectified magnitude at 120% RMT. Reliability was comparatively lower in the seven non-target muscles recorded from the same fixed stimulation site, indicating that MEP consistency was not uniform across the lower-limb musculature. Conclusions: MEP reliability in the lower extremity depends heavily on the muscle, stimulation intensity, and quantification method used, and is highest in the muscle for which the stimulation site was optimized. These findings support the interpretation that coil positioning targeted to a specific muscle yields more consistent responses in that muscle than in others recorded from the same fixed site, and underscore the importance of careful muscle selection and hotspot optimization when designing TMS protocols for longitudinal or clinical lower-limb research.

Ethnopharmacological relevance: Australian Indigenous medicinal plants represent a valuable yet underexplored source of bioactive compounds with potential therapeutic relevance. The Iningai community of Central Queensland has traditionally used native plants to manage conditions associated with inflammation, pain, infection, and general illness. Scientific evaluation of these plants may provide evidence for their customary applications and identify bioactivities relevant to anticancer biodiscovery. Aim of the study: This study evaluated leaf and stem extracts of seven medicinal plants-Pittosporum angustifolium, Alphitonia excelsa, Calytrix microcoma, Geijera parviflora, Melaleuca uncinata, Gossypium australe, and Eucalyptus similis-traditionally used by the Iningai community, focusing on three biological processes relevant to cancer: oxidative stress, inflammation, and cellular proliferation. Materials and methods: Antioxidant activity was assessed using DPPH radical-scavenging and ferric reducing antioxidant power (FRAP) assays. Anti-inflammatory activity was evaluated in lipopolysaccharide (LPS)-stimulated THP-1 macrophage-like cells by profiling IFN-, TNF-, IL-6, IL-12, IL-18, and IL-23. Antiproliferative activity was assessed using MTT-based viability assays in human and murine liver cancer cell lines (Huh7, Hep3B, Hep-55.1c, and A52). Results: The extracts exhibited distinct biological activity profiles. G. parviflora stem and C. microcoma leaf extracts showed the strongest antioxidant activities, whereas P. angustifolium stem exhibited the weakest radical-scavenging capacity. Cytokine responses were extract-specific, with E. similis leaf extract demonstrating broad and pronounced suppression of multiple LPS-induced pro-inflammatory cytokines. Several extracts produced concentration-dependent reductions in liver cancer cell viability, with P. angustifolium stem exhibiting the most consistent and potent antiproliferative activity across the cell lines tested. Notably, strong antioxidant or anti-inflammatory activity did not necessarily correspond with antiproliferative activity. Conclusion: Australian Indigenous medicinal plant extracts demonstrated distinct antioxidant, immunomodulatory, and antiproliferative activities rather than uniform bioactivity across experimental systems. The divergent activities of G. parviflora, C. microcoma, E. similis, and P. angustifolium highlight the importance of integrated biological screening and support the value of Indigenous knowledge-guided biodiscovery. These plants represent promising sources for further investigation of selective bioactive compounds with potential relevance to anticancer drug discovery.

OBJECTIVE: To prioritize novel measures of disease progression, we examined whether actigraphy-derived rest-activity rhythm (RAR) parameters relate to cognitive performance as well as disability in a multiple sclerosis (MS) cohort enrolled in a prospective brain donation program. METHODS: RAR parameters were assessed using a wrist actigraphy device (AX3 Axivity Actiwatch, Axivity Ltd.) over two weeks. The primary outcome measure was the Symbol Digit Modalities Test (SDMT, N=222). Secondary outcomes included Brixton Spatial Anticipation Test and self-reported disability. In 76 participants, volumetric measures were derived from repurposed clinical magnetic resonance imaging (MRI) data. We applied linear and logistic regression models, adjusting for age, sex, education, time since MS diagnosis, and body mass index. RESULTS: After correction for multiple comparisons, higher intradaily variability (IV) of RAR and lower relative amplitude were associated with worse SDMT performance; higher IV was also associated with greater odds of disability. A broader set of RAR parameters was associated with disability measure. No MRI parameters were related to RAR in the subset of individuals with available MRI data, although we note suggestive associations with hippocampal and choroid plexus volumes warranting further investigation. INTERPRETATION: More robust circadian rhythms were related to better cognition. These results highlight the utility of actigraphy and its more nuanced measures beyond the simple summaries of activity levels that quantitate the extent of motor disability. Selected RAR features may be an effective non-invasive approach to capture clinically relevant quantitative measures of brain function for persons with MS.

Automated lesion segmentation is increasingly central to PSMA PET/CT interpretation, supporting staging, treatment planning, and response assessment at a scale that outpaces available nuclear-medicine expertise. However, automated PSMA-PET/CT whole-body lesion segmentation models are trained on images alone, with no knowledge of where in the body prostate metastases actually tend to occur. Radiologists use clinical domain knowledge of metastatic spread, but its absence in machine learning models produces false positives in anatomically implausible locations and missed lesions in high-risk sites such as the liver. In this work, we explore whether population-level spatial knowledge of metastatic spread can be used to augment deep learning segmentation predictions, and how such a prior should be fused with a network's output, without additional training. We build a data-driven metastasis atlas from 375 expert-annotated whole-body PSMA PET/CT scans and investigate its fusion with a trained segmentation network under a Bayesian framework, in which prediction probabilities from an nnU-Net-based lesion segmentation model serve as the likelihood and the data-driven atlas as the prior. Because metastases occupy only a small fraction of whole-body voxels, the atlas's peak probability is too low, and standard power-scaled or naive Bayesian pooling references lack the tools to deal with this shortcoming. This causes these standard fusion strategies to fail and, in the naive Bayesian case, to sharply degrade performance. We instead derive a calibrated, background-referenced log-odds fusion, one of many possible approaches to combine a population atlas with a deep learning model's predictions, distinct from classical multi-atlas label fusion in that it fuses a single population prior with a trained network's softmax rather than combining several registered atlases. Furthermore, this approach is neutral outside atlas support by construction, reduces exactly to the baseline network when unweighted, and requires no retraining. This atlas fusion significantly improved mean Dice over the baseline nnU-Net on a disjoint internal test set ($+0.011$, Holm-adjusted $p=0.021$) and on an independent external cohort ($+0.0129$, Holm-adjusted $p=3.8\times10^{-16}$), with lesion sensitivity improving from 0.849 to 0.861 internally and Dice improving over baseline in every stratified anatomic region, including the rare, high-risk sites motivating this work, while naive Bayesian pooling degrades performance sharply and power-scaled pooling underperforms it throughout. Our findings suggest that population-level spatial priors can meaningfully augment deep learning predictions in whole-body oncologic segmentation, provided the fusion rule is calibrated to where the prior actually carries signal.

Label-free Raman imaging of living cells is photon limited: at exposures compatible with cellular dynamics, single-pixel spectra carry about one count per channel on a dominant smooth background. We present an unmixing framework in which the decoder of a physics-constrained autoencoder is restricted to a data-driven spectroscopic dictionary: band centers,widths, and pseudo-Voigt shapes are measured from the dataset and fixed, and the network learns only nonnegative band amplitudes, a smooth B-spline background, and a per-pixel gain.First, on slit-scanning images of HeLa cells (532 nm) the dictionary yields spike-free component spectra that read as band tables, including a resonance-enhanced cytochrome-c-associated component matching literature spectra, and the most stable decomposition against the component number. Second, the dictionary and initialization calibrated at 1 s exposure perline transfer to 100 ms per line (12 s sweeps): cytochrome-c spectral identity survives a single sweep (correlation 0.92) while its map remains photon limited; the dictionary provides spectral physicality, and the transferred initialization prevents a structural collapse that global map correlations miss; in a measurement-derived phantom the dictionary estimator holds thecytochrome-c spectrum to 17-19{degrees} spectral angle at 100 ms, where classical factorizations and free decoders lose it (55-64{degrees}). Estimation on the count-equivalent detector output uses a calibrated shifted-Poisson quasi-likelihood. Third, evaluation must be time matched:correlation against a separately acquired reference saturates through slow specimen drift and acquisition mismatch rather than photon noise, and the self-consistency of learned denoisers is inflated by shared bias; time-matched self-consistency and independent cross-checks areproposed.

Abstract Objective: Glaucoma is a chronic disorder that impairs ocular health and may exacerbate ocular surface disease leading to tear film instability, dry eye symptoms and decreased quality of life. This study compared changes in tear quantity among glaucoma subjects living with and without diabetes mellitus, attending an eye clinic in Nigeria. Methods: A comparative cross sectional research design was used. 157 subjects which comprised 74 glaucoma subjects living with diabetes mellitus and 83 glaucoma subjects living without diabetes mellitus participated in the study. Tear quantity assessment included the Schirmer I test and tear meniscus height (TMH) measurement. Descriptive statistics, independent samples t-test and Chi-square test were used to examine the data at 0.05 level of significance. Results: Glaucoma subjects living with diabetes mellitus showed substantially decreased tear production (11.4 +/- 6.8 mm) compared with glaucoma subjects living without diabetes mellitus (19.6 +/- 9.6 mm; p < 0.001). Tear meniscus height in glaucoma subjects living with diabetes mellitus (0.8 +/- 0.3 mm) was significantly greater than in subjects living without diabetes mellitus (0.7 +/- 0.3 mm; p = 0.034). Conclusion: Diabetes mellitus dramatically deteriorates the ocular surface function in glaucoma subjects by decreasing tear production, altering the tear meniscus height and increasing the severity of ocular surface symptoms. Routine glaucoma care, especially in patients with diabetes mellitus, should include a full ocular surface evaluation including Schirmer I test, TBUT, TMH, and OSDI assessment to allow early detection and management of ocular surface disease, better treatment adherence, and improved visual outcomes. Keywords: Glaucoma, Diabetes Mellitus, Tear production, Tear Meniscus Height, Ocular Surface Disease.

Purpose: To evaluate the safety, procedural performance, sample recovery, and surgeon preference of an ophthalmic needle designed specifically for anterior chamber (AC) paracentesis. Methods: In this multicenter study, AC paracentesis was performed in clinic and operating-room settings using a 32-gauge x 4-mm needle with low dead space. The procedure was evaluated using a standardized physician survey. Prespecified outcomes included procedure-related adverse events (primary outcome), needle entry and handling, aspiration and sample recovery, comparative performance versus a 30-gauge needle, and physician preference for future use. Results: A total of 110 needle uses by eight surgeons were included. No ocular complications occurred, including lens or iris injury, hyphema, AC collapse, wound leak, hypotony, infection, or retinal complication, and no procedure required needle exchange or conversion to another device. Two technical events without ocular sequelae were noted, in which needle entry was partial thickness and did not reach the AC (1.8%; exact 95% CI, 0.2%-6.4%). Physicians rated needle entry, handling and sample recovery as good or excellent. Compared with a 30-gauge needle, the study needle was rated as at least comparable across all assessed domains. All surgeons rated it better or much better for intra-procedural safety and preferred it for future AC taps. Conclusions and Relevance: This short, 32-gauge low-dead-space ophthalmic needle demonstrated a favorable safety profile and was preferred over a 30-gauge needle by all surgeons. As aqueous humor liquid biopsy expands in clinical diagnostics and trials, an ophthalmic-specific needle design may help improve the consistency and safety of aqueous humor collection for molecular analysis and broader clinical use. Keywords: Anterior chamber paracentesis; Aqueous humor; Liquid biopsy; Low dead space; Ophthalmic needle