Cardiovascular complications are a leading cause of perioperative adverse outcomes, particularly in patients with pre-existing cardiovascular disease. Anaesthesiologists routinely assess cardiovascular risk preoperatively, yet the use of cardiovascular magnetic resonance (CMR) findings in this context remains unclear. This study evaluated how anaesthesiologists perceive and use preexisting CMR findings for perioperative risk evaluation. We conducted an online survey for anaesthesiologists. The primary endpoint was incorporation of CMR findings into perioperative decision-making, with secondary analyses examining factors associated with CMR use and understanding of CMR parameters. A total of 455 anaesthesiologists from 32 countries completed the survey. Most were board certified (84%), and 56% indicated cardiovascular or thoracic anaesthesiology (CVA) as a clinical activity. Overall, 68% reported incorporating findings from CMR reports for perioperative risk assessment at least sometimes, with no difference in use between respondents specialising in CVA and those who do not (69% vs 67%; odds ratio 1.17 [95% confidence interval 0.84-1.63]; P=0.36). Although left ventricular anatomy and function were widely incorporated (72%), understanding of advanced tissue characterisation markers was limited, particularly among non-CVA anaesthesiologists. Notably, 74% agreed that CMR holds potential for perioperative risk evaluation, and 54% expressed interest in its future integration. Among respondents to this voluntary survey, CMR findings were frequently reported as being incorporated into perioperative risk evaluation, including those without CVA specialisation. However, use remains focused on conventional functional metrics, with limited knowledge of advanced CMR markers. Further research linking CMR parameters to perioperative outcomes, alongside targeted education initiatives, is needed to enable evidence-based implementation in anaesthetic practice.
Hepatocellular carcinoma (HCC) is a biologically heterogeneous malignancy staged according to tumor burden and clinical status. Molecular and histopathologic factors remain unincorporated into current staging systems, as they are usually unavailable because HCC is often diagnosed noninvasively. Emerging evidence indicates that magnetic resonance imaging (MRI) features reflect underlying tumor biology and provide prognostic information beyond diagnosis. MRI can differentiate proliferative-class HCC, which is characterized by aggressive behavior, frequent microvascular invasion (MVI), and poor outcomes, from non-proliferative-class HCC with more favorable biology. Several MRI features, including rim arterial phase hyperenhancement (APHE), non-smooth margins, necrosis, intratumoral arteries, low apparent diffusion coefficient, peritumoral APHE, and peritumoral hepatobiliary phase (HBP) hypointensity, have been associated with aggressive tumor behavior and adverse outcomes. In contrast, capsule appearance, intratumoral fat, and HBP hyperintensity are associated with more favorable biology. Although biopsy is not routinely required when characteristic imaging features of HCC are present, imaging features suggestive of aggressive tumor subtypes may identify patients who could benefit from histologic confirmation for diagnostic clarification, molecular profiling, or treatment planning. Radiomics and artificial intelligence-based analyses further enhance MVI prediction, recurrence risk stratification, and noninvasive molecular characterization. In conclusion, the emerging role of MRI in characterizing tumor biology underscores the growing importance of imaging biomarkers in clinical decision-making and selective biopsy strategies.
Cardiac magnetic resonance elastography (MRE) is an emerging modality for noninvasive assessment of left ventricular (LV) myocardial stiffness. Accurate LV myocardium delineation is essential for MRE analysis, yet current workflows often rely on manual annotation and additional structural MRI. It remains uncertain whether native cardiac MRE data alone are sufficient for reliable automated LV segmentation. To evaluate deep learning approaches for LV myocardium segmentation on cardiac MRE data and to assess the influence of input representation and automation strategy on segmentation performance. Cardiac MRE data from 16 healthy male volunteers were used to train and evaluate two contemporary segmentation frameworks, nnU-Net v2 and MedSAM. Reader 1 annotated the full dataset using MRE magnitude images, and Reader 2 independently annotated the test set, enabling model performance to be benchmarked against inter-reader agreement. nnU-Net was trained using multiple input representations and training strategies. MedSAM was evaluated in zero-shot, semi-automated, fine-tuned, autoprompt, and box-regression configurations. Inter-reader Dice agreement was 0.79 ± 0.03. The best nnU-Net model, trained on fully averaged normalized magnitude images, achieved a Dice score of 0.82 ± 0.04. Performance was lower with magnitude-plus-phase and real-plus-imaginary inputs, with Dice scores of 0.65 ± 0.21 and 0.60 ± 0.20, respectively, and also decreased with non-normalized magnitude input, which yielded a Dice score of 0.75 ± 0.05. The best MedSAM result was obtained with a semi-automated fine-tuned variant using strong ROI smoothing, which achieved a Dice score of 0.82 ± 0.02. Fully automated MedSAM variants performed less well, with Dice scores of 0.68 ± 0.09 for autoprompt and 0.71 ± 0.08 for box regression. Cardiac MRE data alone demonstrated the feasibility of accurate LV myocardium segmentation, with nnU-Net and MedSAM both reaching inter-reader-level performance. These findings support direct segmentation of the LV myocardium from native cardiac MRE and represent a step toward a self-contained cardiac MRE workflow.
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Chikungunya virus (CHIKV) causes severe acute and chronic disease, yet no approved specific antiviral treatment exists. To rapidly identify potential treatments, we aimed to screen an FDA-approved drug library for inhibitors of CHIKV infection. Tirbanibulin, a dual-microtubule polymerization and Src kinase inhibitor, was assessed for its potential anti-CHIKV activity. We performed a high-throughput screen of an FDA-approved drug library. Mechanism-of-action studies included entry-step analysis, surface plasmon resonance (SPR) binding assays and molecular docking. In vivo efficacy was evaluated in lethal murine neuroinfection and CHIKV-induced arthritis models following oral administration of the candidate compound. Tirbanibulin exhibited nanomolar to low-micromolar antiviral activity (EC50 range: 0.035-75.64 μM) across multiple cell lines, with high selective indices in key target HT22 and Huh7 cells. It acted at a post-attachment entry step, inhibiting clathrin-mediated endocytosis and potentially viral fusion. Surface plasmon resonance confirmed direct, high-affinity binding to the CHIKV E1 and E2 glycoprotein complex (K_D = 73 nM). In the lethal neuroinfection model, oral tirbanibulin significantly improved survival and reduced brain viral loads; in the arthritis model, it markedly attenuated footpad swelling and inflammatory pathology. Tirbanibulin is a novel, orally bioavailable entry-stage inhibitor that directly targets the E2 glycoprotein. Multiple preclinical and clinical studies have confirmed its favourable oral bioavailability and safety. Given its established clinical safety profile, it represents a promising repurposing candidate for clinical evaluation against Chikungunya fever.
Distal triceps tendon injuries are uncommon but clinically significant, typically occurring after heavy eccentric loading and resulting in loss of active elbow extension. Complete ruptures are traditionally treated with surgical repair using transosseous tunnels or suture anchors; however, high retear rates have been reported following traditional repair techniques. Bio-inductive collagen implants have demonstrated efficacy in augmenting rotator cuff repair by promoting neovascularization and tissue regeneration; however, their use in distal triceps tendon injuries has not been previously reported. A 59-year-old male agricultural worker with a history of tobacco use presented with an acute complete distal triceps tendon rupture sustained while climbing into farm equipment. Physical examination revealed an inability to actively extend the elbow against resistance and a palpable defect over the distal triceps tendon. Magnetic resonance imaging confirmed a full-thickness tear with 1.5 cm of proximal tendon retraction from the olecranon insertion. The patient underwent open surgical repair using two suture anchors with a whipstitch technique augmented with a resorbable bio-inductive collagen implant secured over the repair site. At two weeks postoperatively, the surgical incision was well-healed without complications. By six weeks, the patient achieved active elbow motion from 10° to 90° of flexion. After three months, a full range of motion and near-normal triceps strength were restored. At one-year follow-up, magnetic resonance imaging demonstrated complete implant resorption, intact tendon continuity, and no evidence of retear. No adverse immunological reactions or postoperative complications were observed. This case demonstrates the technical feasibility and safety of bio-inductive collagen implant augmentation in distal triceps tendon repair, with excellent functional recovery at one-year follow-up. These findings provide a proof-of-concept for the use of bio-inductive augmentation in distal triceps repair and support further investigation in larger comparative studies.
Alzheimer's disease is a complex neurodegenerative disorder and the leading cause of dementia worldwide. Learning-based techniques applied to magnetic resonance imaging (MRI) have recently shown strong potential for automated diagnosis. Accurate classification typically relies on high-resolution (HR) 3D MRI acquired with thin axial slices to reduce partial-volume artefacts, capture fine anatomical details, and improve diagnostic performance. However, acquiring such data is time-consuming, costly, and prone to motion artefacts and patient discomfort. Super-resolution methods offer a promising alternative by reconstructing HR 3D images from lower-resolution scans and enabling shorter acquisition times. In this study, we propose a novel pipeline that applies super-resolution to through-plane undersampled 3D magnetic resonance images and demonstrates that the resulting volumes preserve Alzheimer's disease diagnostic accuracy comparable to that achieved using fully sampled HR scans. We compare different state-of-the-art super-resolution methods from distinct methodological families, with the best-performing method achieving an F1 score of 65.6, close to the HR reference of 65.7 and substantially higher than the low-resolution baseline of 55.9. Furthermore, we investigate whether standard image quality metrics (e.g. pixel-based metrics) are sufficient to assess the contribution of super-resolution to the clinical evaluation of Alzheimer's disease. To this end, we compare them with machine learning-based measures, such as maximum mean discrepancy, and surface-based metrics derived from segmented anatomical structures, highlighting their limitations in clinically oriented evaluations.
Accurate and efficient three-dimensional visualization of cerebral vasculature is essential for clinical evaluation; however, manual vessel extraction from time-of-flight (TOF) magnetic resonance angiography angiography (MRA) is time-consuming and operator-dependent. This study aimed to develop a deep learning-based cerebrovascular segmentation model and an automated vessel extraction method, and to evaluate their accuracy, volumetric reliability, and impact on volume rendering (VR) workflow efficiency. A 3D U-Net-based vessel segmentation model was trained using TOF-MRA images. Automated vessel extraction was performed by dilating predicted vessel regions by one voxel. Forty-eight intracranial aneurysm cases were analyzed. Segmentation performance was evaluated using the Dice similarity coefficient (DSC), normalized surface Dice (NSD); tolerance = 1 mm), and centerline distance (CLD). Inter-rater reliability was assessed using DSC between independently generated vessel masks in a subset of the dataset. Aneurysm volumes from original and vessel-extracted images were compared using equivalence testing with a 1% margin and two one-sided tests (TOST). VR image creation time was measured by 12 radiological technologists. The DSC between independently generated vessel masks was 0.916. The DSC, recall, and precision of dilated vessel masks were significantly higher than those of non-dilated masks (p < 0.0001). The NSD was 0.982 ± 0.015, and the CLD was 0.196 ± 0.182 mm. Aneurysm volumes showed strong correlation (r = 0.999) with a small mean absolute error (MAE) (0.0915 mm³), and equivalence by TOST (p < 0.001). VR image creation time was significantly reduced (p = 0.0130). The proposed method enables accurate, reproducible, and time-efficient generation of cerebral vascular VR images, suggesting its potential utility in clinical practice.
Healing dynamics after anterior skull base (ASB) reconstruction following transnasal endoscopic surgery (TES) for sinonasal malignancies remain poorly characterized. This study aimed to describe the postoperative healing process, quantify time to healing, identify factors influencing healing, and assess radiologic evolution over time. This multicenter retrospective study included adult patients undergoing TES with craniectomy and ASB reconstruction for sinonasal malignancies between 2016 and 2024. Serial endoscopic examinations were reviewed using a novel stage-based classification system. Postoperative contrast-enhanced magnetic resonance imaging (MRI) was analyzed to evaluate reconstruction layers, enhancement patterns, thickness changes, and brain sagging. Cumulative incidence analysis, multistate modeling, and uni- and multivariable analyses were performed to identify factors associated with healing. A total of 173 patients were included. Complete endoscopic healing was achieved in 15.9% of patients at 6 months, 69.9% at 12 months, and 94.4% at 24 months. Local pedicled flap reconstruction was associated with faster healing, with complete healing achieved in 89.4% of patients at 12 months compared with 60.7% in graft-based reconstructions (p < 0.001). Adjuvant radiotherapy (RT), particularly intensity-modulated proton therapy, was independently associated with delayed healing. MRI showed progressive reduction in reconstruction thickness, decreased visibility of adipose tissue and the outer graft layer, and increased brain sagging over time. RT was associated with greater remodeling changes, whereas flap-based reconstruction appeared to mitigate these effects. Healing after ASB reconstruction following TES is a prolonged and dynamic process influenced mainly by reconstruction technique and adjuvant RT. Local vascularized flaps promote faster and more stable healing and may be particularly advantageous in patients requiring postoperative RT.
Predicting cognitive decline as a continuum, from healthy age-related decline to mild cognitive impairment and dementia, enables more precise individual-level predictions. However, the practical value of such models for early intervention and prevention depends on their ability to generalize to independent cohorts, a property that is often not evaluated. This study investigated whether adding structural magnetic resonance imaging (MRI) to non-brain data improved machine learning predictions of continuous cognitive decline and analyzed the models' generalizability. Multi-target random forest regression models predicted annual decline in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SOB) and Mini-Mental State Examination (MMSE) using non-brain data, structural MRI data, or their combination from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1237) and Open Access Series of Imaging Studies (OASIS-3; N = 662) datasets. Cross-site generalizability was evaluated. Data from ADNI and OASIS-3 were used for this study. A total of 1899 participants who had demographic, clinical, and brain imaging data from a baseline session and clinical data from at least 2 follow-up sessions were included. Baseline non-brain (demographics, clinical and neuropsychological scores, information on APOE genotype, cognitive diagnosis, health, and number of sessions before baseline) and/or structural MRI data were used to predict the yearly rate of change in CDR-SOB and MMSE scores. Including structural MRI data improved prediction of CDR-SOB and MMSE change, reaching respective R2 values of .41 and .33 in ADNI and .42 and .33 in OASIS-3. Model performance for across-dataset predictions was reduced (R2 between .18 and .35), unexplained by distributional shifts of target variables. Models using only top predictive features performed similarly to full models when tested externally (R2 between .18 and .34), suggesting predictor redundancy. Incorporating structural MRI data enhances within-dataset prediction of continuous cognitive decline, allowing for more precise individual-level prediction and advancing towards precision medicine. Even though external validation remains limited, quantifying the generalizability gap is a crucial step towards the responsible use of ML models in clinical intervention and prevention.
Introduction The timing of dental implant placement following tooth extraction is an important clinical consideration because it may influence osseointegration and functional rehabilitation. Although both early and delayed implant placement protocols are widely used, evidence regarding their effects on implant stability and masticatory function is limited. This study aimed to compare early and delayed dental implant placements in terms of implant stability and bite force. Materials and methods This prospective observational study was conducted at the Department of Prosthodontics, K. M. Shah Dental College and Hospital, Sumandeep Vidyapeeth (Deemed to be University), Vadodara, Gujarat, India. Sixty patients were categorized into two groups of 30 participants in each group. The early implant group received implants four to eight weeks after tooth extraction, whereas the delayed implant group underwent implant placement after a minimum healing period of six months. Implant stability was assessed using resonance frequency analysis (RFA) and expressed as implant stability quotient (ISQ) values. Functional rehabilitation was evaluated by measuring the bite force using a digital occlusal force analyzer. Assessments were performed at baseline and six months after prosthetic loading. Statistical analyses were conducted using paired and independent t-tests, with statistical significance set at p < 0.05. Results Both groups demonstrated significant improvements in implant stability and bite force over the six-month follow-up period (p = 0.001). In the early implant group, the mean ISQ values increased from 62.4 ± 4.8 to 74.6 ± 3.9, whereas the delayed implant group showed an increase from 58.7 ± 5.2 to 71.2 ± 4.6. The bite force increased from 128.4 ± 22.6 N to 218.3 ± 31.4 N in the early implant group and from 134.7 ± 25.1 N to 204.6 ± 28.9 N in the delayed implant group. The early implant group demonstrated significantly higher implant stability at baseline and six months (p < 0.05). Although the bite force values at individual time points were comparable between the groups, the increase in bite force over time was significantly greater in the early implant group (p = 0.006). Conclusions Both early and delayed implant placement protocols achieved successful osseointegration and functional rehabilitation in the present study. However, early implant placement demonstrated superior implant stability and greater improvement in bite force, suggesting that it may provide favorable clinical outcomes when appropriate case selection and treatment planning are performed.
Mitral valve blood cysts are rare, benign lesions in adults. A 52-year-old female presenting with acute ischemic stroke was found on echocardiography to have a thin-walled, mobile, 1.2 × 2.4 cm cystic mass on the posterior mitral leaflet, along with hypertrophic obstructive cardiomyopathy. Although transesophageal echocardiography detected the mass, differentiating it from solid tumors or caseous calcifications remained challenging. Noncontrast cardiac magnetic resonance imaging showed that the cyst's internal signal was isointense with the left ventricular blood pool throughout the cardiac cycle. This distinct dynamic signature definitively ruled out solid neoplasms and caseous mitral annular calcification, confirming a blood-filled cavity.
Preterm birth influences early functional brain maturation at term-equivalent age. Using resting-state functional magnetic resonance imaging from a large Chinese neonatal cohort (62 term-born and 107 preterm neonates), we examined static and dynamic network organization using multi-level graph-theoretical analyses. Preterm neonates exhibited reduced global integration and segregation, reflected by lower global efficiency, clustering coefficient, and local efficiency, together with increased characteristic path length. Widespread nodal and modular alterations were observed across multiple networks. Dynamic analyses revealed selective edge-level disturbances involving the right parahippocampal gyrus and its connections with default mode, visual, and limbic networks, despite limited group differences in global or nodal dynamic metrics. Developmental analyses further showed associations between specific global metrics and postmenstrual age at scan. Network measures were also associated with prenatal factors, including multiple pregnancy and cesarean delivery. These findings characterize early alterations in static and dynamic functional network organization after preterm birth and highlight prenatal factors potentially related to neonatal brain development.
A wearable cardioverter-defibrillator (WCD) provides noninvasive and temporary protection against sudden cardiac death (SCD) in patients at transient risk of ventricular arrhythmias, including myocarditis. We report the case of a 68-year-old man with recurrent wide QRS complex tachycardia (WCT) and myocarditis confirmed by cardiac magnetic resonance imaging, who was discharged with a WCD following in-hospital stabilization. During the one-month follow-up, the device detected 200 WCT episodes, lasting up to 50 seconds and reaching rates of 150 beats per minute, despite clinical improvement and recovery of left ventricular ejection fraction (from 47% to 52%). An electrophysiological study revealed orthodromic atrioventricular reentrant tachycardia mediated by a retrogradely conducting accessory pathway (AP), reproducing the WCT morphology recorded by the WCD. Radiofrequency ablation of AP successfully eliminated the arrhythmia. This case highlights the diagnostic value of prolonged electrocardiographic monitoring with WCD beyond protection from malignant arrhythmia, enabling timely intervention and avoidance of unnecessary implantable cardioverter-defibrillator implantation.
Magnetic resonance imaging (MRI) is regarded as the clinical diagnostic gold standard. However, its lengthy scan times introduce motion artifacts, which can severely compromise diagnostic accuracy. K-space undersampling is a fundamental strategy to address this issue, but undersampling inevitably introduces quality degradation in reconstructed images. To tackle the challenges in accelerated MRI reconstruction, this paper proposes a Multi-Feature Guided Progressive Divide-and-Conquer reconstruction network (MFG-PDAC). It achieves synergistic optimization through three novel modules. The Multi-Frequency Gated Attention (MFGA) module enhances feature propagation, the Edge Enhanced Feature Modulation (EEFM) module reinforces anatomical boundaries, and the Frequency-Aware Data Consistency (FREDC) module optimizes spectral reconstruction. These three modules form a closed-loop mechanism consisting of feature selection, spatial optimization, and frequency-domain correction. The MFGA enables dynamic fusion of multi-frequency features at U-Net skip connections, providing structural priors for gradient modulation. The gradient modulation amplifies edge response in the image domain, improving high-frequency reconstruction quality. The FREDC dynamically weights constraints based on frequency band errors, creating a feedback mechanism for MFGA refinement. Evaluated on the fast MRI knee dataset, MFG-PDAC achieved a peak signal-to-noise ratio of 37.28 dB and structural similarity index measurement of 0.909 under 8× acceleration, outperforming the current mainstream methods. The network particularly can achieve better reconstruction in key diagnostic regions such as bone-soft tissue interfaces and ligament textures. This study provides an accurate and efficient solution for clinical rapid MRI scanning, demonstrating significant potential for clinical translation.
Longitudinal studies of seed-based functional connectivity (SBFC) in young adult Huntington's disease gene-expanded (HDGE) individuals are rare, and none, to our knowledge, have examined adult cohorts decades from predicted clinical motor diagnosis. To examine longitudinal functional connectivity (FC) changes over ~4.8 years in adult HDGE individuals before clinical motor diagnosis compared with matched controls, all selected from the HD Young Adult Study (HD-YAS) cohort, focusing on bilateral caudate and putamen as seeds. A subset of 71 right-handed individuals (43 HDGEs and 28 controls) from the HD-YAS underwent resting-state functional magnetic resonance imaging (fMRI) at two visits ~4.8 years apart. SBFC analyses focused on bilateral caudate and putamen seeds. Mixed-effects analysis of variance (ANOVA) tested main effects of group, time, and group × time interactions, with false discovery rate (FDR) correction. Post hoc tests explored significant findings. HDGEs showed reduced FC between the putamen and cerebellar vermis/lobules and brainstem (P-FDR ≤ 0.01), alongside increased connectivity with precuneus (P-FDR = 0.04), supramarginal, and angular gyri (P-FDR = 0.04). Over ~4.8 years, HDGEs exhibited different FC trajectories compared with controls, displaying FC reductions between the right caudate and paracingulate, frontal (P-FDR = < 0.001), occipital (P-FDR = < 0.01), and striatal regions (P-FDR = ≤ 0.03). These findings provide the first longitudinal evidence of early cortico-striatal and cerebellar functional network changes in adult HDGEs decades before clinical motor diagnosis, alongside possible compensatory processes in key hubs of the default mode network. These early FC changes likely reflect a dynamic interplay between neurodegenerative processes and adaptive reorganization, a balance that may ultimately fail as pathology progresses. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Cyanobacterial blooms in hyper-eutrophic lakes are managed through nitrogen-to-phosphorus (N:P) control, yet single-axis nutrient reduction has often been insufficient to achieve sustained bloom suppression in shallow systems such as Lake Taihu, China. We hypothesised that the missing management dimension is spatial: free-living (FL, 0.22-3 µm) and particle-attached (PA, >3 µm) fractions may deploy distinct nutrient-acquisition machineries under the same bulk N:P. Native Lake Taihu assemblages were cultured at four N:P molar ratios (5, 16, 23, 40; TN fixed at 2.0 mg N L⁻¹; TP adjusted to 0.886, 0.277, 0.192, and 0.111 mg P L⁻¹, respectively) for 28 days, then sequentially filtered and analysed by 16S amplicon sequencing, shotgun metagenomics and 15-T Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) of dissolved organic matter (24 paired-fraction biomass samples + 8 DOM samples). Three key findings emerged. First, FL and PA carry the genetic potential for chemically distinct phosphorus-acquisition strategies (hereafter termed the P-currency split): FL is enriched in the high-affinity inorganic-Pi transporter genes pstSCAB (dominated by Synechococcus), whereas PA carries the genetic potential to mobilise organic P via phoD and ugpQ (dominated by Bacteroidota); the PstS + Ppk1 dual-wheel hypothesis was not supported under fraction-resolved testing. Second, PA harbours the genetic potential for a consistent nitrogen-cycle hotspot across all N:P levels, with nifH enriched 1.8-5.0-fold in PA and 87% attributable to the heterotroph Porphyrobacter. Third, Synechococcus shows an apparent stoichiometric niche-shift from FL dominance at N:P = 23 (43.8%) to PA dominance at N:P = 40 (54.1%). Together, the joint N:P × fraction model explained 95.8% of community variance (Mantel r = 0.963 within PA). These findings identify the phoD-anchored Bacteroidota guild and PA-aggregate disruption as candidate fraction-resolved management levers that complement conventional nutrient reduction in shallow eutrophic lakes.
We examined liver and muscle glycogen utilisation during high-intensity interval cycling, and the impact of carbohydrate (CHO) feeding, using non-invasive 13C magnetic resonance spectroscopy (MRS). Following 24 h of standardised dietary intake, nine male cyclists completed 8 x 5-min intervals (1-min recovery), ingesting either placebo (PLA), 60 g maltodextrin (CHO) or 60 g maltodextrin plus caffeine, taurine, l-theanine, l-citrulline and citicoline (CHO+) in a randomised crossover design. 13C MRS and 1H imaging were performed pre- and post-exercise to determine liver and muscle glycogen and liver volume, respectively. Liver glycogen utilisation was not significantly different between trials (P = 0.101) despite lower post-exercise plasma glucagon concentrations in CHO and CHO+ (P = 0.001). In contrast, muscle glycogen utilisation was significantly lower (~40%) with CHO feeding compared to PLA (P = 0.006) yet this sparing effect was not evident with CHO+ (P = 0.073) in accordance with a higher mean power output during the late intervals (+ 2.8%, P = 0.046). Plasma glucose was comparable between trials (P = 0.175) whereas plasma lactate was higher in CHO+ vs CHO (P = 0.003), alongside lower blood bicarbonate (P = 0.005), base excess (P <0.001) and total CO2 (P = 0.004). These findings demonstrate preferential use of skeletal muscle glycogen during HIIT, which is attenuated under conditions of CHO feeding. This sparing effect is, however, not evident with the co-ingestion of a caffeine containing multi-ingredient blend, potentially due to an increased capacity to sustain higher power outputs resulting in greater glycogen utilisation.
Spontaneous intracranial hypotension (SIH) is commonly caused by spinal cerebrospinal fluid (CSF) leakage. Microspur-related ventral dural tears are an increasingly recognized etiology of SIH; however, lumbar lesions remain extremely rare. A 41-year-old woman presented with severe orthostatic headache and nausea. Whole-spine magnetic resonance imaging demonstrated spinal longitudinal extradural CSF collection (SLEC), suggesting spinal CSF leakage. Computed tomography myelography identified a small calcified lesion at the L1/2 level consistent with a discogenic microspur compressing the ventral dural sac. Digital subtraction myelography (DSM) demonstrated active contrast extravasation into the epidural space at the corresponding level, consistent with a ventral dural tear caused by the microspur. Targeted epidural blood patch treatment at the L1/2 level resulted in rapid symptom resolution without recurrence during 18 months of follow-up. This case demonstrates that lumbar microspurs can cause SLEC-positive SIH through ventral dural injury. DSM was useful for dynamic localization of the active CSF leak and facilitated targeted treatment. To the best of our knowledge, this is the first reported case of lumbar microspur-induced SIH confirmed by DSM.
A switchable supramolecular solvent based dispersive liquid-liquid microextraction method was developed for the preconcentration and determination of six main hepatotoxic ingredients in Chinese herbal medicine of "Psoraleae Fructus" combined with high performance liquid chromatography-ultraviolet detection. Based on the biodegradable alkyl polyglucoside and a switchable deep eutectic solvent composed of diethanolamine and hexanoic acid, a hydrophilic supramolecular solvent was prepared for the extraction of the target analytes from the aqueous sample solution, and the phase separation was obtained by adding hydrochloric acid solution. A combination of one-factor-at-a-time and central composite design was employed to investigate the primary factors influencing the extraction efficiency, including the composition and volume of alkyl polyglucoside-based switchable supramolecular solvent, the type and dosage of phase-switching trigger, extraction time and salt concentration of the sample solution. Under the optimal extraction conditions, the performance metrics of the proposed method were validated, demonstrating good linearity (r ≥ 0.9979), low detection limits, satisfactory precisions (relative standard deviation≤6.4%) and spiked recoveries (90.3%-107.8%). The enrichment factors for six target analytes ranged from 64 to 666 greater than the published reports. The formation of the supramolecular solvent was characterized by utilizing Fourier transform infrared spectroscopy and proton nuclear magnetic resonance spectroscopy. The extraction mechanism was elucidated by analytes properties, theoretical calculation and the molecular docking. The greenness of the proposed method was assessed by AGREE and AGREEprep tools. The established method possessed good extraction efficiency and could effectively enrich the components with varying polarities in complex matrices.