Effects of component ratios on the properties of sweet potato-oat composite dough and the quality of its steamed cake.

To enhance the value proposition of sweet potato and oat while broadening their applicability in further processing, this study systematically investigated the impact of oat flour incorporation ratios (5%-25% of sweet potato dry weight) on the quality attributes of sweet potato-oat composite dough and its resulting steamed cake products. The results showed that the addition of oat flour could promote the rheological, water retention, and thermomechanical properties of the composite dough and improve the internal microstructure, specific volume, texture, and other processing properties of the steamed cake products. The rheology, water retention, and protein stability of the dough were maximized when the proportion of oat flour was 25%. The textural properties of steamed cakes, hardness, elasticity, cohesion, adhesion, chewiness, and recovery significantly increased (p < 0.05) and viscosity significantly decreased (p < 0.05) with the addition of oat flour. It is noteworthy that thermodynamic properties, internal structure of the dough, and air holding capacity, which are critical for processing, showed the best results at 20% oat flour addition. Therefore, the addition of 20%-25% oats is recommended to produce composite doughs with optimal quality and processing characteristics. PRACTICAL APPLICATION: As living standards improve, traditional cereals may no longer able to meet people's health needs. Therefore, there is an urgent consumer demand for nutritious, tasty alternatives to staple foods. In this study, oat flour and sweet potato mash were mixed to make sweet potato-oat cake, and the effect of ingredient ratio on the performance and quality of composite dough containing sweet potato-oat flour was analyzed, thus proposing an innovative approach to the research, development, and industrial production of sweet potato and oat food products.

Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI.

Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM Attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies and technical developments of this imaging technique.

Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI.

Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique.

Automatic Brain Tissue and Lesion Segmentation and Multi-Parametric Mapping of Contrast-Enhancing Gliomas without the Injection of Contrast Agents: A Preliminary Study.

This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inversion pulses throughout incomplete inversion recovery in a single 6 min scan. Modified k-means clustering was performed for automatic brain tissue and lesion segmentation using distinct signal evolutions that contained mixed T1/T2/magnetization transfer properties. Multi-compartment modeling was used to derive quantitative multi-parametric maps for tissue characterization. Fourteen patients with contrast-enhancing gliomas were scanned with this sequence prior to the injection of a contrast agent, and their segmented lesions were compared to conventionally defined manual segmentations of T2-hyperintense and contrast-enhancing lesions. Simultaneous T1, T2, and macromolecular proton fraction maps were generated and compared to conventional 2D T1 and T2 mapping and myelination water fraction mapping acquired with MAGiC. The lesion volumes defined with the new method were comparable to the manual segmentations (r = 0.70, p < 0.01; t-test p > 0.05). The T1, T2, and macromolecular proton fraction mapping values of the whole brain were comparable to the reference values and could distinguish different brain tissues and lesion types (p < 0.05), including infiltrating tumor regions within the T2-lesion. Highly efficient, whole-brain, multi-contrast imaging facilitated automatic lesion segmentation and quantitative multi-parametric mapping without contrast, highlighting its potential value in the clinic when gadolinium is contraindicated.

Current methods for hyperpolarized [1-13C]pyruvate MRI human studies.

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of HP agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate-by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation; (2) MRI system setup and calibrations; (3) data acquisition and image reconstruction; and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the "HP 13C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods and Equipment study groups. It further aims to provide a comprehensive reference for future consensus, building as the field continues to advance human studies with this metabolic imaging modality.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach.

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

Altered Iron and Microstructure in Huntington's Disease Subcortical Nuclei: Insight From 7T MRI.

BACKGROUND: Pathophysiological changes of Huntington's disease (HD) can precede symptom onset by decades. Robust imaging biomarkers are needed to monitor HD progression, especially before the clinical onset. PURPOSE: To investigate iron dysregulation and microstructure alterations in subcortical regions as HD imaging biomarkers, and to associate such alterations with motor and cognitive impairments. STUDY TYPE: Prospective. POPULATION: Fourteen individuals with premanifest HD (38.0 ± 11.0 years, 9 females; far-from-onset N = 6, near-onset N = 8), 21 manifest HD patients (49.1 ± 12.1 years, 11 females), and 33 age-matched healthy controls (43.9 ± 12.2 years, 17 females). FIELD STRENGTH/SEQUENCE: 7 T, T1 -weighted imaging, quantitative susceptibility mapping, and diffusion tensor imaging. ASSESSMENT: Volume, susceptibility, fractional anisotropy (FA), and mean diffusivity (MD) within subcortical brain structures were compared across groups, used to establish HD classification models, and correlated to clinical measures and cognitive assessments. STATISTICAL TESTS: Generalized linear model, multivariate logistic regression, receiver operating characteristics with the area under the curve (AUC), and likelihood ratio test comparing a volumetric model to one that also includes susceptibility and diffusion metrics, Wilcoxon paired signed-rank test, and Pearson's correlation. A P-value <0.05 after Benjamini-Hochberg correction was considered statistically significant. RESULTS: Significantly higher striatal susceptibility and FA were found in premanifest and manifest HD preceding atrophy, even in far-from-onset premanifest HD compared to controls (putamen susceptibility: 0.027 ± 0.022 vs. 0.018 ± 0.013 ppm; FA: 0.358 ± 0.048 vs. 0.313 ± 0.039). The model with additional susceptibility, FA, and MD features showed higher AUC compared to volume features alone when differentiating premanifest HD from HC (0.83 vs. 0.66), and manifest from premanifest HD (0.94 vs. 0.83). Higher striatal susceptibility significantly correlated with cognitive deterioration in HD (executive function: r = -0.600; socioemotional function: r = -0.486). DATA CONCLUSION: 7 T MRI revealed iron dysregulation and microstructure alterations with HD progression, which could precede volume loss, provide added value to HD differentiation, and might be associated with cognitive changes. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Characterization and Antioxidant Activity of the Polysaccharide Hydrolysate from Lactobacillus plantarum LPC-1 and Their Effect on Spinach (Spinach oleracea L.) Growth.

This study presents a comparison between two hydrolysis systems (MnO2/H2O2 and ascorbic acid (VC)/H2O2) for the depolymerization of exopolysaccharide (EPS) from Lactobacillus plantarum LPC-1. Response surface methodology (RSM) was used to optimize these two degradation systems, resulting in two H2O2-free degradation products, MEPS (MnO2/H2O2-treated EPS) and VEPS (VC/H2O2-treated EPS), where H2O2 residues in the final products and their antioxidant activity were considered vital points. The relationship between the structural variations of two degraded polysaccharides and their antioxidant activity was characterized. Physicochemical tests showed that H2O2 had a notable impact on determining the total and reducing sugars in the polysaccharides, and both degradation systems efficiently eliminated this effect. After optimization, the average molecular weight of EPS was reduced from 265.75 kDa to 135.41 kDa (MEPS) and 113.11 kDa (VEPS), improving its antioxidant properties. Characterization results showed that the two hydrolysis products had similar major functional groups and monosaccharide composition as EPS. The crystal structure, main chain length, and branched chain number were crucial factors affecting the biological activity of polysaccharides. In pot testing, two degraded polysaccharides improved spinach quality more than EPS due to their lower molecular weights, suggesting the advantages of low-molecular-weight polysaccharides. In summary, these two degradation techniques offer valuable insights for further expanding the utilization of microbial resources.

Dynamic T 2 * relaxometry of hyperpolarized [1-13 C]pyruvate MRI in the human brain and kidneys.

PURPOSE: This study aimed to quantify T 2 * $$ {T}_2^{\ast } $$ for hyperpolarized [1-13 C]pyruvate and metabolites in the healthy human brain and renal cell carcinoma (RCC) patients at 3 T. METHODS: Dynamic T 2 * $$ {T}_2^{\ast } $$ values were measured with a metabolite-specific multi-echo spiral sequence. The dynamic T 2 * $$ {T}_2^{\ast } $$ of [1-13 C]pyruvate, [1-13 C]lactate, and 13 C-bicarbonate was estimated in regions of interest in the whole brain, sinus vein, gray matter, and white matter in healthy volunteers, as well as in kidney tumors and the contralateral healthy kidneys in a separate group of RCC patients. T 2 * $$ {T}_2^{\ast } $$ was fit using a mono-exponential function; and metabolism was quantified using pyruvate-to-lactate conversion rate maps and lactate-to-pyruvate ratio maps, which were compared with and without an estimated T 2 * $$ {T}_2^{\ast } $$ correction. RESULTS: The T 2 * $$ {T}_2^{\ast } $$ of pyruvate was shown to vary during the acquisition, whereas the T 2 * $$ {T}_2^{\ast } $$ of lactate and bicarbonate were relatively constant through time and across the organs studied. The T 2 * $$ {T}_2^{\ast } $$ of lactate was similar in gray matter (29.75 ± 1.04 ms), white matter (32.89 ± 0.9 ms), healthy kidney (34.61 ± 4.07 ms), and kidney tumor (33.01 ± 2.31 ms); and the T 2 * $$ {T}_2^{\ast } $$ of bicarbonate was different between whole-brain (108.17 ± 14.05 ms) and healthy kidney (58.45 ± 6.63 ms). The T 2 * $$ {T}_2^{\ast } $$ of pyruvate had similar trends in both brain and RCC studies, reducing from 75.56 ± 2.23 ms to 22.24 ± 1.24 ms in the brain and reducing from 122.72 ± 9.86 ms to 57.38 ± 7.65 ms in the kidneys. CONCLUSION: Multi-echo dynamic imaging can quantify T 2 * $$ {T}_2^{\ast } $$ and metabolism in a single integrated acquisition. Clear differences were observed in the T 2 * $$ {T}_2^{\ast } $$ of metabolites and in their behavior throughout the timecourse.

Estimate of fetal brain temperature using proton resonance frequency thermometry during 3 Tesla fetal magnetic resonance imaging.

Background: T2-weighted Single Shot Fast Spin Echo (SSFSE) scans at 3 Tesla (3T) are increasingly used to image fetal pathology due to their excellent tissue contrast resolution and signal-to-noise ratio (SNR). Temperature changes that may occur in response to radio frequency (RF) pulses used for these sequences at 3T have not been studied in human fetal brains. To evaluate the safety of T2-weighted SSFSE for fetal brains at 3T, magnetic resonance (MR) thermometry was used to measure relative temperature changes in a typical clinical fetal brain MR exam. Methods: Relative temperature was estimated using sets of gradient recalled echo (GRE) images acquired before and after T2-weighted SSFSE images which lasted 27.47±8.19 minutes. Thirty-one fetuses with cardiac abnormalities, and 20 healthy controls were included in this study. Fetal brain temperature was estimated by proton resonance frequency (PRF) thermometry and compared to the estimated temperature in the gluteal muscle of the mother. Seven scans with excessive motion were excluded. Local outlier factor (LOF) was performed to remove 12 additional scans with spurious phase measurements due to motion degradation and potential field drift. Linear regression was performed to determine if temperature changes are dependent on the rate of energy deposition during the scan. Results: For the 32 participants used in the analysis, 17 with cardiac abnormalities and 15 healthy controls, the average relative fetal temperate change was 0.19±0.73 ℃ higher than the mother, with no correlation between relative temperature change and the rate of images acquired during the scans (regression coefficient =-0.05, R-squared =0.05, P=0.22, F-statistic =1.60). The difference in the relative temperature changes between the fetal brain and mother's gluteal tissue in the healthy controls was on average 0.08 ℃ lower and found not to be statistically different (P=0.76) to the group with cardiac abnormalities. Conclusions: Our results indicate that the estimated relative temperature changes of the fetal brain compared to the mother's gluteal tissue from RF pulses during the course of the T2-weighted SSFSE fetal MR exam are minimal. The differences in acquired phase between these regions through the exam were found not to be statistically different. These findings support that fetal brain imaging at 3T is within FDA limits and safe.

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates.

OBJECTIVES: Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphometrics in third trimester is associated with postnatal abnormalities and neurodevelopmental outcome. METHODS: In total, 577 T1 MRI scans of preterm neonates from two different datasets were analyzed; the NEOCIVET pipeline generated cortical surfaces and morphological features, which were then fed to the GCN to predict brain age. The brain age index (BAI; PBA minus chronological age) was used to determine the relationships among preterm birth (i.e., birthweight and birth age), perinatal brain injuries, postnatal events/clinical conditions, BAI at postnatal scan, and neurodevelopmental scores at 30 months. RESULTS: Brain morphology and GCN-based age prediction of preterm neonates without brain lesions (mean absolute error [MAE]: 0.96 weeks) outperformed conventional machine learning methods using no topological information. Structural equation models (SEM) showed that BAI mediated the influence of preterm birth and postnatal clinical factors, but not perinatal brain injuries, on neurodevelopmental outcome at 30 months of age. CONCLUSIONS: Brain morphology may be clinically meaningful in measuring brain age, as it relates to postnatal factors, and predicting neurodevelopmental outcome. CLINICAL RELEVANCE STATEMENT: Understanding the neurodevelopmental trajectory of preterm neonates through the prediction of brain age using a graph convolutional neural network may allow for earlier detection of potential developmental abnormalities and improved interventions, consequently enhancing the prognosis and quality of life in this vulnerable population. KEY POINTS: •Brain age in preterm neonates predicted using a graph convolutional network with brain morphological changes mediates the pre-scan risk factors and post-scan neurodevelopmental outcomes. •Predicted brain age oriented from conventional deep learning approaches, which indicates the neurodevelopmental status in neonates, shows a lack of sensitivity to perinatal risk factors and predicting neurodevelopmental outcomes. •The new brain age index based on brain morphology and graph convolutional network enhances the accuracy and clinical interpretation of predicted brain age for neonates.

Fetal circulatory physiology and brain development in complex congenital heart disease: A multi-modal imaging study.

OBJECTIVE: Fetuses with complex congenital heart disease have altered physiology, contributing to abnormal neurodevelopment. The effects of altered physiology on brain development have not been well studied. We used multi-modal imaging to study fetal circulatory physiology and brain development in hypoplastic left heart syndrome (HLHS) and d-transposition of the great arteries (TGA). METHODS: This prospective, cross-sectional study investigated individuals with fetal congenital heart disease and controls undergoing fetal echocardiography and fetal brain MRI. MRI measured total brain volume and cerebral oxygenation by the MRI quantification method T2*. Indexed cardiac outputs (CCOi) and vascular impedances were calculated by fetal echocardiography. Descriptive statistics assessed MRI and echocardiogram measurement relationships by physiology. RESULTS: Sixty-six participants enrolled (control = 20; HLHS = 25; TGA = 21), mean gestational age 33.8 weeks (95% CI: 33.3-34.2). Total brain volume and T2* were significantly lower in fetuses with cardiac disease. CCOi was lower in HLHS, correlating with total brain volume - for every 10% CCOi increase, volume increased 8 mm3 (95% CI: 1.78-14.1; p = 0.012). Echocardiography parameters and cerebral oxygenation showed no correlation. TGA showed no CCOi or aortic output correlation with MRI measures. CONCLUSIONS: In HLHS, lower cardiac output is deleterious to brain development. Our findings provide insight into the role of fetal cardiovascular physiology in brain health.

Atlas-Based Adaptive Hadamard-Encoded MR Spectroscopic Imaging at 3T.

BACKGROUND: This study aimed to develop a time-efficient method of acquiring simultaneous, dual-slice MR spectroscopic imaging (MRSI) for the evaluation of brain metabolism. METHODS: Adaptive Hadamard-encoded pulses were developed and integrated with atlas-based automatic prescription. The excitation profiles were evaluated via simulation, phantom and volunteer experiments. The feasibility of γ-aminobutyric acid (GABA)-edited dual-slice MRSI was also assessed. RESULTS: The signal between slices in the dual-band MRSI was less than 1% of the slice profiles. Data from a homemade phantom containing separate, interfacing compartments of creatine and acetate solutions demonstrated ~0.4% acetate signal contamination relative to the amplitude in the excited creatine compartment. The normalized signal-to-noise ratios from atlas-based acquisitions in volunteers were found to be comparable between dual-slice, Hadamard-encoded MRSI and 3D acquisitions. The mean and standard deviation of the coefficients of variation for NAA/Cho from the repeated volunteer scans were 8.2% ± 0.8% and 10.1% ± 3.7% in the top and bottom slices, respectively. GABA-edited, dual-slice MRSI demonstrated simultaneous detection of signals from GABA and coedited macromolecules (GABA+) from both superior grey and deep grey regions of volunteers. CONCLUSION: This study demonstrated a fully automated dual-slice MRSI acquisition using atlas-based automatic prescription and adaptive Hadamard-encoded pulses.

Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human Studies.

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the "HP 13C MRI Consensus Group" as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods & Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.

Evaluation of deep learning models for quality control of MR spectra.

Purpose: While 3D MR spectroscopic imaging (MRSI) provides valuable spatial metabolic information, one of the hurdles for clinical translation is its interpretation, with voxel-wise quality control (QC) as an essential and the most time-consuming step. This work evaluates the accuracy of machine learning (ML) models for automated QC filtering of individual spectra from 3D healthy control and patient datasets. Methods: A total of 53 3D MRSI datasets from prior studies (30 neurological diseases, 13 brain tumors, and 10 healthy controls) were included in the study. Three ML models were evaluated: a random forest classifier (RF), a convolutional neural network (CNN), and an inception CNN (ICNN) along with two hybrid models: CNN + RF, ICNN + RF. QC labels used for training were determined manually through consensus of two MRSI experts. Normalized and cropped real-valued spectra was used as input. A cross-validation approach was used to separate datasets into training/validation/testing sets of aggregated voxels. Results: All models achieved a minimum AUC of 0.964 and accuracy of 0.910. In datasets from neurological disease and controls, the CNN model produced the highest AUC (0.982), while the RF model achieved the highest AUC in patients with brain tumors (0.976). Within tumor lesions, which typically exhibit abnormal metabolism, the CNN AUC was 0.973 while that of the RF was 0.969. Data quality inference times were on the order of seconds for an entire 3D dataset, offering drastic time reduction compared to manual labeling. Conclusion: ML methods accurately and rapidly performed automated QC. Results in tumors highlights the applicability to a variety of metabolic conditions.

Investigating cerebral perfusion with high resolution hyperpolarized [1-13 C]pyruvate MRI.

PURPOSE: To investigate high-resolution hyperpolarized (HP) 13 C pyruvate MRI for measuring cerebral perfusion in the human brain. METHODS: HP [1-13 C]pyruvate MRI was acquired in five healthy volunteers with a multi-resolution EPI sequence with 7.5 × 7.5 mm2 resolution for pyruvate. Perfusion parameters were calculated from pyruvate MRI using block-circulant singular value decomposition and compared to relative cerebral blood flow calculated from arterial spin labeling (ASL). To examine regional perfusion patterns, correlations between pyruvate and ASL perfusion were performed for whole brain, gray matter, and white matter voxels. RESULTS: High resolution 7.5 × 7.5 mm2 pyruvate images were used to obtain relative cerebral blood flow (rCBF) values that were significantly positively correlated with ASL rCBF values (r = 0.48, 0.20, 0.28 for whole brain, gray matter, and white matter voxels respectively). Whole brain voxels exhibited the highest correlation between pyruvate and ASL perfusion, and there were distinct regional patterns of relatively high ASL and low pyruvate normalized rCBF found across subjects. CONCLUSION: Acquiring HP 13 C pyruvate metabolic images at higher resolution allows for finer spatial delineation of brain structures and can be used to obtain cerebral perfusion parameters. Pyruvate perfusion parameters were positively correlated to proton ASL perfusion values, indicating a relationship between the two perfusion measures. This HP 13 C study demonstrated that hyperpolarized pyruvate MRI can assess cerebral metabolism and perfusion within the same study.

Preparation of polysaccharide-conjugated selenium nanoparticles from spent mushroom substrates and their growth-promoting effect on rice seedlings.

Selenium nanoparticles (SeNPs) have gained significant attention in the agricultural field due to their favorable bioavailability and low toxicity, making them a highly researched subject. In this study, crude polysaccharides from spent mushroom substrate of Agrocybe aegerita (AaPs) were extracted for preparing the polysaccharide­selenium-nanoparticles (AaPs-SeNPs) by ascorbic acid reduction method. The structure of AaPs-SeNPs was analyzed and their growth-promoting effects on rice seedlings were studied by adopting different application methods. The results revealed that AaPs-SeNPs exhibited improved free radical scavenging ability, with a lower half-maximal inhibitory concentrations compared to AaPs. Rice seedlings treated with AaPs-SeNPs showed significant enhancements in growth characteristics when compared to AaPs treatment, and foliar application exhibited a better growth-promoting effect compared to root application. Moreover, the growth performance and antioxidant enzyme activities of rice seedlings were enhanced by the addition of AaPs-SeNPs, and the absorption efficiency of essential nutrients such as N/P/K and Fe/Zn/Mn was also improved at appropriate concentrations, which could be one of the key factors contributing to the improved growth performance of plants. This study provides new aspects for the utilization of SMS, and also offers new insights from the perspective of nutrient absorption on how polysaccharide-conjugated selenium nanoparticles enhance crop growth.

Multi-parametric hyperpolarized 13C/1H imaging reveals Warburg-related metabolic dysfunction and associated regional heterogeneity in high-grade human gliomas.

BACKGROUND: Dynamic hyperpolarized (HP)-13C MRI has enabled real-time, non-invasive assessment of Warburg-related metabolic dysregulation in glioma using a [1-13C]pyruvate tracer that undergoes conversion to [1-13C]lactate and [13C]bicarbonate. Using a multi-parametric 1H/HP-13C imaging approach, we investigated dynamic and steady-state metabolism, together with physiological parameters, in high-grade gliomas to characterize active tumor. METHODS: Multi-parametric 1H/HP-13C MRI data were acquired from fifteen patients with progressive/treatment-naïve glioblastoma [prog/TN GBM, IDH-wildtype (n = 11)], progressive astrocytoma, IDH-mutant, grade 4 (G4AIDH+, n = 2) and GBM manifesting treatment effects (n = 2). Voxel-wise regional analysis of the cohort with prog/TN GBM assessed imaging heterogeneity across contrast-enhancing/non-enhancing lesions (CEL/NEL) and normal-appearing white matter (NAWM) using a mixed effects model. To enable cross-nucleus parameter association, normalized perfusion, diffusion, and dynamic/steady-state (HP-13C/spectroscopic) metabolic data were collectively examined at the 13C resolution. Prog/TN GBM were similarly compared against progressive G4AIDH+ and treatment effects. RESULTS: Regional analysis of Prog/TN GBM metabolism revealed statistically significant heterogeneity in 1H choline-to-N-acetylaspartate index (CNI)max, [1-13C]lactate, modified [1-13C]lactate-to-[1-13C]pyruvate ratio (CELval > NELval > NAWMval); [1-13C]lactate-to-[13C]bicarbonate ratio (CELval > NELval/NAWMval); and 1H-lactate (CELval/NELval > NAWMundetected). Significant associations were found between normalized perfusion (cerebral blood volume, nCBV; peak height, nPH) and levels of [1-13C]pyruvate and [1-13C]lactate, as well as between CNImax and levels of [1-13C]pyruvate, [1-13C]lactate and modified ratio. GBM, by comparison to G4AIDH+, displayed lower perfusion %-recovery and modeled rate constants for [1-13C]pyruvate-to-[1-13C]lactate conversion (kPL), and higher 1H-lactate and [1-13C]pyruvate levels, while having higher nCBV, %-recovery, kPL, [1-13C]pyruvate-to-[1-13C]lactate and modified ratios relative to treatment effects. CONCLUSIONS: GBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.

Hyperpolarized [2-13C]pyruvate MR molecular imaging with whole brain coverage.

Hyperpolarized (HP) 13C Magnetic Resonance Imaging (MRI) was applied for the first time to image and quantify the uptake and metabolism of [2-13C]pyruvate in the human brain to provide new metabolic information on cerebral energy metabolism. HP [2-13C]pyruvate was injected intravenously and imaged in 5 healthy human volunteer exams with whole brain coverage in a 1-minute acquisition using a specialized spectral-spatial multi-slice echoplanar imaging (EPI) pulse sequence to acquire 13C-labeled volumetric and dynamic images of [2-13C]pyruvate and downstream metabolites [5-13C]glutamate and [2-13C]lactate. Metabolic ratios and apparent conversion rates of pyruvate-to-lactate (kPL) and pyruvate-to-glutamate (kPG) were quantified to investigate simultaneously glycolytic and oxidative metabolism in a single injection.

Using Neonatal Magnetic Resonance Imaging to Predict Gross Motor Disability at Four Years in Term-Born Children With Neonatal Encephalopathy.

BACKGROUND: Children with neonatal encephalopathy (NE) are at risk for basal ganglia/thalamus (BG/T) and watershed patterns of brain injury. Children with BG/T injury are at high risk for motor impairment in infancy, but the predictive validity of a published rating scale for outcome at age four years is not known. We examined a cohort of children with NE and magnetic resonance imaging (MRI) to examine the relationship between BG/T injury and severity of cerebral palsy (CP) in childhood. METHODS: Term-born neonates at risk for brain injury due to NE were enrolled from 1993 to 2014 and received MRI within two weeks of birth. Brain injury was scored by a pediatric neuroradiologist. The Gross Motor Function Classification System (GMFCS) level was determined at four years. The relationship between BG/T injury and dichotomized GMFCS (no CP or GMFCS I to II = none/mild versus III to V = moderate/severe CP) was evaluated with logistic regression, and predictive performance was assessed by cross-validated area under the receiver operating characteristic curve (AUROC). RESULTS: Among 174 children, higher BG/T scores were associated with more severe GMFCS level. Clinical predictors had a low AUROC (0.599), compared with that of MRI (0.895). Risk of moderate to severe CP was low (<20%) in all patterns of brain injury except BG/T = 4, which carried a 67% probability (95% confidence interval 36% to 98%) of moderate to severe CP. CONCLUSIONS: The BG/T injury score can be used to predict the risk and severity of CP at age four years and thereby inform early developmental interventions.