Urinary oxygen tension and its role in predicting acute kidney injury: A narrative review.

Acute kidney injury occurs frequently in the perioperative setting. The renal medulla often endures hypoxia or hypoperfusion and is susceptible to the imbalance between oxygen supply and demand due to the nature of renal blood flow distribution and metabolic rate in the kidney. The current available evidence demonstrated that the urine oxygen pressure is proportional to the variations of renal medullary tissue oxygen pressure. Thus, urine oxygenation can be a candidate for reflecting the change of oxygen in the renal medulla. In this review, we discuss the basic physiology of acute kidney injury, as well as techniques for monitoring urine oxygen tension, confounding factors affecting the reliable measurement of urine oxygen tension, and its clinical use, highlighting its potential role in early detection and prevention of acute kidney injury.

Agreement of zero-heat-flux thermometry with the oesophageal and tympanic core temperature measurement in patient receiving major surgery.

To identify and prevent perioperative hypothermia, most surgical patients require a non-invasive, accurate, convenient, and continuous core temperature method, especially for patients undergoing major surgery. This study validated the precision and accuracy of a cutaneous zero-heat-flux thermometer and its performance in detecting intraoperative hypothermia. Adults undergoing major non-cardiac surgeries with general anaesthesia were enrolled in the study. Core temperatures were measured with a zero-heat-flux thermometer, infrared tympanic membrane thermometer, and oesophagal monitoring at 15-minute intervals. Taking the average value of temperature measured in the tympanic membrane and oesophagus as a reference, we assessed the agreement using the Bland-Altman analysis and linear regression methods. Sensitivity, specificity, and predictive values of detecting hypothermia were estimated. 103 patients and one thousand sixty-eight sets of paired temperatures were analyzed. The mean difference between zero-heat-flux and the referenced measurements was -0.03 ± 0.25 °C, with 95% limits of agreement (-0.52 °C, 0.47 °C) was narrow, with 94.5% of the differences within 0.5 °C. Lin's concordance correlation coefficient was 0.90 (95%CI 0.89-0.92). The zero-heat-flux thermometry detected hypothermia with a sensitivity of 82% and a specificity of 90%. The zero-heat-flux thermometer is in good agreement with the reference core temperature based on tympanic and oesophagal temperature monitoring in patients undergoing major surgeries, and appears high performance in detecting hypothermia.

Role of hydrogels in osteoarthritis: A comprehensive review.

Osteoarthritis (OA) is a chronic, degenerative, and age-related disease. It is characterized by chronic inflammation, progressive articular cartilage destruction, and subchondral bone sclerosis. The current effective treatment for OA is limited. Hydrogel is a kind of unique carrier with well-known biocompatibility, softness, and high water content among various biomaterials. Hydrogels are developed for different biomedical applications, for instance, drug delivery, and tissue engineering. To date, a variety of hydrogels-based therapies have been used in OA patients or animal models. In this review, we comprehensively summarized the potential role of hydrogels in chondrocytes proliferation, apoptosis, and inflammatory component production and discussed the impact of hydrogels on OA development. The collection of this information will help better understand the present progress of hydrogels in OA.

How Does Mitochondrial Protein-Coding Gene Expression in Fejervarya kawamurai (Anura: Dicroglossidae) Respond to Extreme Temperatures?

Unusual climates can lead to extreme temperatures. Fejervarya kawamurai, one of the most prevalent anurans in the paddy fields of tropical and subtropical regions in Asia, is sensitive to climate change. The present study focuses primarily on a single question: how do the 13 mitochondrial protein-coding genes (PCGs) respond to extreme temperature change compared with 25 °C controls? Thirty-eight genes including an extra tRNA-Met gene were identified and sequenced from the mitochondrial genome of F. kawamurai. Evolutionary relationships were assessed within the Dicroglossidae and showed that Dicroglossinae is monophyletic and F. kawamurai is a sister group to the clade of (F. multistriata + F. limnocharis). Transcript levels of mitochondrial genes in liver were also evaluated to assess responses to 24 h exposure to low (2 °C and 4 °C) or high (40 °C) temperatures. Under 2 °C, seven genes showed significant changes in liver transcript levels, among which transcript levels of ATP8, ND1, ND2, ND3, ND4, and Cytb increased, respectively, and ND5 decreased. However, exposure to 4 °C for 24 h was very different in that the expressions of ten mitochondrial protein-coding genes, except ND1, ND3, and Cytb, were significantly downregulated. Among them, the transcript level of ND5 was most significantly downregulated, decreasing by 0.28-fold. Exposure to a hot environment at 40 °C for 24 h resulted in a marked difference in transcript responses with strong upregulation of eight genes, ranging from a 1.52-fold increase in ND4L to a 2.18-fold rise in Cytb transcript levels, although COI and ND5 were reduced to 0.56 and 0.67, respectively, compared with the controls. Overall, these results suggest that at 4 °C, F. kawamurai appears to have entered a hypometabolic state of hibernation, whereas its mitochondrial oxidative phosphorylation was affected at both 2 °C and 40 °C. The majority of mitochondrial PCGs exhibited substantial changes at all three temperatures, indicating that frogs such as F. kawamurai that inhabit tropical or subtropical regions are susceptible to ambient temperature changes and can quickly employ compensating adjustments to proteins involved in the mitochondrial electron transport chain.

Two-Fold ND5 Genes, Three-Fold Control Regions, lncRNA, and the "Missing" ATP8 Found in the Mitogenomes of Polypedates megacephalus (Rhacophridae: Polypedates).

In prior research on the mitochondrial genome (mitogenome) of Polypedates megacephalus, the one copy of ND5 gene was translocated to the control region (CR) and the ATP8 gene was not found. Gene loss is uncommon among vertebrates. However, in this study, we resequenced the mitogenomes of P. megacephalus from different regions using a "primer bridging" approach with Sanger sequencing technologies, which revealed the "missing" ATP8 gene in P. megacephalus as well as three other previously published Polypedates. The mitogenome of this species was found to contain two copies of the ND5 genes and three copies of the control regions. Furthermore, multiple tandem repeats were identified in the control regions. Notably, we observed that there was no correlation between genetic divergence and geographic distance. However, using the mitogenome, gene expression analysis was performed via RT-qPCR of liver samples and it was thus determined that COIII, ND2, ND4, and ND6 were reduced to 0.64 ± 0.24, 0.55 ± 0.34, 0.44 ± 0.21 and 0.65 ± 0.17, respectively, under low-temperature stress (8 °C) as compared with controls (p < 0.05). Remarkably, the transcript of long non-coding RNA (lncRNA) between positions 8029 and 8612 decreased significantly with exposure to low-temperature stress (8 °C). Antisense ND6 gene expression showed a downward trend, but this was not significant. These results reveal that modulations of protein-coding mitochondrial genes and lncRNAs of P. megacephalus play a crucial role in the molecular response to cold stress.

Licorice zinc suppresses melanogenesis via inhibiting the activation of P38MAPK and JNK signaling pathway in C57BL/6J mice skin.

PURPOSE: The active melanocytes in the skin were affected by hormones and ultraviolet (UV) irradiation. Licorice zinc has a whitening effect, which may have a prominent potential in the treatment of pigmented skin disease. METHODS: Modeling chloasma C57BL/6J mice by daily progesterone injection (15 mg/kg) and ultraviolet B (UVB) irradiation (λ = 312 nm, 2 h/day) for 30 days. Then, mice were given 0.65, 1.3, and 2.6 (g/kg) of licorice zinc and tranexamic acid 250 mg daily by oral administration for 14 days, respectively. Hematoxylin and eosin and Fontana-Masson staining, and Western blotting (WB) were performed to test the inhibitory of melanogenesis and activation of c-Jun-N-terminal (JNK)/p38 mitogen-activated protein kinases (MAPK) for licorice zinc. Melanogenesis was induced by α-melanocyte-stimulating hormone in vitro. Cell counting kit-8, melanin content determination, and WB were performed to verify the inhibitory effect of licorice zinc on melanogenesis. RESULTS: The present study showed that licorice zinc decreased melanin formation, cutaneous tissue injury, and the phosphorylation of JNK and P38MAPK, which was caused by UVB irradiation in vivo. In vitro, licorice zinc showed opposite effects from JNK/p38 activator. Meanwhile, tyrosinase-related protein-1, tyrosinase, and microphthalmia-associated transcription factor were decreased too. CONCLUSIONS: Licorice zinc induced a decrease in melanin synthesis by inhibiting the JNK and the P38MAPK signaling pathway, suggesting licorice zinc is a potential agent of anti-chloasma.

[Preparation and characterization of near-infrared responsive sinomenine hydrochloride reservoir microneedles].

The present study designed and prepared near-infrared responsive sinomenine hydrochloride(SIN) reservoir microneedles and evaluated the feasibility of this type of microneedles in increasing the drug loading and transdermal absorption by characterizing their mechanical properties and in vitro release characteristics.SIN was selected as the model drug, and methoxy poly(ethylene glycol) poly(caprolactone)(mPEG-PCL) copolymers and indocyanine green(ICG) were employed as amphiphilic block copolymers and light inductor to prepare near-infrared responsive nanoparticles.Based on the preparation principle of bubble microneedles, near-infrared responsive SIN reservoir microneedles were designed and prepared.The features of the near-infrared responsive SIN reservoir microneedles were characterized by measuring the morphology, length, mechanical properties, and skin penetration of microneedles.Meanwhile, the drug release performance of reservoir microneedles was evaluated by in vitro release assay.The results showed that the prepared SIN microneedles were conical, with an exposed tip height of about 650 µm.Each needle could load about 0.5 mg of drugs per square centi-meter, and this type of microneedle showed good mechanical properties and performance in skin penetration.The results of the in vitro release assay showed that the 24 h cumulative release per unit area and release rate of the microneedle were 825.61 µg·cm~(-2) and 74.3%, respectively, which indicated that its release kinetics was in line with the first-order kinetic model.This study preliminarily proved that the reservoir microneedle could effectively increase the drug loading with good mechanical properties and release perfor-mance.

[Enhancing effect and mechanism of muscone on transdermal penetration of traditional Chinese medicine ingredients with different log P value].

This study aimed to investigate the enhancing effect of muscone on the transdermal penetration of traditional Chinese medicine ingredients and explore its possible mechanism of action. The Franz diffusion cells were employed to investigate the effect of muscone on the transdermal permeation of a series of model drugs with a wide range of log P values. The solubilities at saturation and the stratum corneum(SC)/vehicle partition coefficients of model drugs were measured to evaluate the effect of muscone on drug thermodynamic activities and partition of drugs into SC. Attenuated total reflectance-Fourier transform infrared spectroscopy(ATR-FTIR) was employed to explore the effect of muscone on the molecular structure of SC. The results showed that muscone significantly promoted the transdermal penetration of hydrophilic and lipophilic drugs, and the enhancement ratio(ER) increased with the decrease in the log P. Muscone could interact with the SC lipids to increase the disorder and fluidity of lipid bilayer packing, which improved skin permeability and promoted transdermal absorption of drugs. This study provides a scientific basis for the application of muscone in traditional Chinese medicine topical preparations.

Management and implementation strategies of pre-screening triage in children during coronavirus disease 2019 pandemic in Guangzhou, China.

BACKGROUND: Emerging infectious diseases are a constant threat to the public's health and health care systems around the world. Coronavirus disease 2019 (COVID-2019), which was defined by the World Health Organization as pandemic, has rapidly emerged as a global health threat. Outbreak evolution and prevention of international implications require substantial flexibility of frontline health care facilities in their response. AIM: To explore the effect of the implementation and management strategy of pre-screening triage in children during COVID-19. METHODS: The standardized triage screening procedures included a standardized triage screening questionnaire, setup of pre-screening triage station, multi-point temperature monitoring, extensive screenings, and two-way protection. In order to ensure the implementation of the pre-screening triage, the prevention and control management strategies included training, emergency exercise, and staff protection. Statistical analysis was performed on the data from all the children hospitalized from January 20, 2020 to March 20, 2020 at solstice during the pandemic period. Data were obtained from questionnaires and electronic medical record systems. RESULTS: A total of 17561 children, including 2652 who met the criteria for screening, 192 suspected cases, and two confirmed cases without omission, were screened from January 20, 2020 to March 20, 2020 at solstice during the pandemic period. There was zero transmission of the infection to any medical staff. CONCLUSION: The effective strategies for pre-screening triage have an essential role in the prevention and control of hospital infection.

Transbrachial Access for Transcatheter Closure of Paravalvular Leak Following Prosthetic Valve Replacement.

Background: Transcatheter closure of paravalvular leak (PVL) has evolved into an alternative to surgery in high-risk patients. In this study, we introduce a new access for transcatheter closure of PVL and seek to evaluate the feasibility and safety of this access. Methods: We retrospectively analyzed patients undergoing transbrachial access for transcatheter mitral or aortic PVL closure (August 2017-November 2019) at our hospital. All patients underwent puncture of the brachial artery under local anesthesia. Results: The study population included 11 patients, with an average age of 55.91 ± 14.82 years. Ten out of 11 patients were successfully implanted with devices via the brachial artery approach, and one patient was converted to the transseptal approach. The technical success rate of transbrachial access was 90.9%. Mean NYHA functional class improved from 3.1 ± 0.5 before the procedure to 1.9 ± 0.5 after PVL closure. Severe paravalvular regurgitation (PVR) in five patients and moderate PVR in six patients prior to the procedure were significantly reduced to mild in four patients and none in seven patients after the procedure. Complications included one case of pseudoaneurysm and one case of moderate hemolysis aggravation after closure. One patient had an unknown cause of sudden death within 24 h after the procedure. The half-year mortality rate during follow-up was 9.1% (1/11). Conclusions: Transbrachial access for transcatheter closure of PVL may be a feasible and safe treatment and should include well-selected patients. It has several potential advantages of simplifying the procedure process and reducing postprocedural bed rest time.

Ectopic expression of an AGAMOUS homologue gene in Jatropha curcas causes early flowering and heterostylous phenotypes.

Jatropha curcasseeds are abundant in biodiesel, and low seed yields are linked to poor quality female flowers, which creates a bottleneck for Jatropha seed utilization. Therefore, identifying the genes associated with flowering is crucial for the genetic enrichment of seed yields. Here, we identified an AGAMOUS homologue gene (JcAG) from J. curcas. We found that reproductive organs had higher JcAG expression than vegetative organs, particularly the carpel. Rosette leaves were small and misshapen in 35S:JcAG transgenic lines in comparison with those in wild-type plants. JcAG overexpression caused an extremely early flowering, delayed perianth and stamen filament development, small flowers, and significantly shorter Arabidopsis plants with little fruit. In the JcAG-overexpressing line, the homeotic transformation of sepals into pistillate organs was observed, and floral meristem and organ identity genes were regulated. This study provides insights into the JcAG's function and benefits to our knowledge of the underlying the genetic mechanisms related to floral sex differentiation in Jatropha.

Query-Specific Deep Embedding of Content-Rich Network.

In this paper, we propose to embed a content-rich network for the purpose of similarity searching for a query node. In this network, besides the information of the nodes and edges, we also have the content of each node. We use the convolutional neural network (CNN) to represent the content of each node and then use the graph convolutional network (GCN) to further represent the node by merging the representations of its neighboring nodes. The GCN output is further fed to a deep encoder-decoder model to convert each node to a Gaussian distribution and then convert back to its node identity. The dissimilarity between the two nodes is measured by the Wasserstein distance between their Gaussian distributions. We define the nodes of the network to be positives if they are relevant to the query node and negative if they are irrelevant. The labeling of the positives/negatives is based on an upper bound and a lower bound of the Wasserstein distances between the candidate nodes and the query nodes. We learn the parameters of CNN, GCN, encoder-decoder model, Gaussian distributions, and the upper bound and lower bounds jointly. The learning problem is modeled as a minimization problem to minimize the losses of node identification, network structure preservation, positive/negative query-specific relevance-guild distance, and model complexity. An iterative algorithm is developed to solve the minimization problem. We conducted experiments over benchmark networks, especially innovation networks, to verify the effectiveness of the proposed method and showed its advantage over the state-of-the-art methods.

Evaluation of the Combination of Azithromycin and Naphthoquine in Animal Malaria Models.

Combination therapy using drugs with different mechanisms of action is the current state of the art in antimalarial treatment. However, except for artemisinin-based combination therapies, only a few other combinations are now available. Increasing concern regarding the emergence and spread of artemisinin resistance in Plasmodium falciparum has led to a need for the development of new antimalarials. Moreover, the efficacy of current available chemoprophylaxis is compromised by drug resistance and noncompliance due to intolerable adverse effects or complicated dosing regimens. Therefore, new antimalarials that are more effective, safer, and more convenient are also urgently needed for malaria chemoprophylaxis. In this study, we assessed the combination of azithromycin and naphthoquine in animal malaria models. A dose-dependent interaction was observed in Peters' 4-day suppressive test on P. berghei K173-infected mice. Moreover, at inhibition levels of ≥90%, synergistic effects were found for combinations at various ratios. At an optimal dose ratio of 1:1, the combination of azithromycin and naphthoquine acted synergistically even by 4 weeks after the first dose and provided a more effective and sustained prophylaxis than did naphthoquine alone in blood-stage P. berghei K173 and P. cynomolgibastianelli L challenge models. The ability of the combination to delay and slow down resistance development in P. berghei K173 was also shown. These results showed clear evidence for the benefit of the combination therapy with azithromycin and naphthoquine in animal malaria models, providing some insight for further development of this therapy for malaria treatment and prophylaxis.

Iterative Deep Neighborhood: A Deep Learning Model Which Involves Both Input Data Points and Their Neighbors.

Deep learning models, such as deep convolutional neural network and deep long-short term memory model, have achieved great successes in many pattern classification applications over shadow machine learning models with hand-crafted features. The main reason is the ability of deep learning models to automatically extract hierarchical features from massive data by multiple layers of neurons. However, in many other situations, existing deep learning models still cannot gain satisfying results due to the limitation of the inputs of models. The existing deep learning models only take the data instances of an input point but completely ignore the other data points in the dataset, which potentially provides critical insight for the classification of the given input. To overcome this gap, in this paper, we show that the neighboring data points besides the input data point itself can boost the deep learning model's performance significantly and design a novel deep learning model which takes both the data instances of an input point and its neighbors' classification responses as inputs. In addition, we develop an iterative algorithm which updates the neighbors of data points according to the deep representations output by the deep learning model and the parameters of the deep learning model alternately. The proposed algorithm, named "Iterative Deep Neighborhood (IDN)," shows its advantages over the state-of-the-art deep learning models over tasks of image classification, text sentiment analysis, property price trend prediction, etc.

De novo transcriptome assembly for the five major organs of Zanthoxylum armatum and the identification of genes involved in terpenoid compound and fatty acid metabolism.

BACKGROUND: Zanthoxylum armatum (Z. armatum) is a highly economically important tree that presents a special numbing taste. However, the underlying regulatory mechanism of the numbing taste remains poorly understood. Thus, the elucidation of the key genes associated with numbing taste biosynthesis pathways is critical for providing genetic information on Z. armatumand the breeding of high-quality germplasms of this species. RESULTS: Here, de novo transcriptome assembly was performed for the five major organs of Z. armatum, including the roots, stems, leaf buds, mature leaves and fruits. A total of 111,318 unigenes were generated with an average length of 1014 bp. Additionally, a large number of SSRs were obtained to improve our understanding of the phylogeny and genetics of Z. armatum. The organ-specific unigenes of the five major samples were screened and annotated via GO and KEGG enrichment analysis. A total of 53 and 34 unigenes that were exclusively upregulated in fruit samples were identified as candidate unigenes for terpenoid biosynthesis or fatty acid biosynthesis, elongation and degradation pathways, respectively. Moreover, 40 days after fertilization (Fr4 stage) could be an important period for the accumulation of terpenoid compounds during the fruit development and maturation of Z. armatum. The Fr4 stage could be a key point at which the first few steps of the fatty acid biosynthesis process are promoted, and the catalysis of subsequent reactions could be significantly induced at 62 days after fertilization (Fr6 stage). CONCLUSIONS: The present study realized de novo transcriptome assembly for the five major organs of Z. armatum. To the best of our knowledge, this study provides the first comprehensive analysis revealing the genes underlying the special numbing taste of Z. armatum. The assembled transcriptome profiles expand the available genetic information on this species and will contribute to gene functional studies, which will aid in the engineering of high-quality cultivars of Z. armatum.

Learning Domain-Independent Deep Representations by Mutual Information Minimization.

Domain transfer learning aims to learn common data representations from a source domain and a target domain so that the source domain data can help the classification of the target domain. Conventional transfer representation learning imposes the distributions of source and target domain representations to be similar, which heavily relies on the characterization of the distributions of domains and the distribution matching criteria. In this paper, we proposed a novel framework for domain transfer representation learning. Our motive is to make the learned representations of data points independent from the domains which they belong to. In other words, from an optimal cross-domain representation of a data point, it is difficult to tell which domain it is from. In this way, the learned representations can be generalized to different domains. To measure the dependency between the representations and the corresponding domain which the data points belong to, we propose to use the mutual information between the representations and the domain-belonging indicators. By minimizing such mutual information, we learn the representations which are independent from domains. We build a classwise deep convolutional network model as a representation model and maximize the margin of each data point of the corresponding class, which is defined over the intraclass and interclass neighborhood. To learn the parameters of the model, we construct a unified minimization problem where the margins are maximized while the representation-domain mutual information is minimized. In this way, we learn representations which are not only discriminate but also independent from domains. An iterative algorithm based on the Adam optimization method is proposed to solve the minimization to learn the classwise deep model parameters and the cross-domain representations simultaneously. Extensive experiments over benchmark datasets show its effectiveness and advantage over existing domain transfer learning methods.

Low-Rank Deep Convolutional Neural Network for Multitask Learning.

In this paper, we propose a novel multitask learning method based on the deep convolutional network. The proposed deep network has four convolutional layers, three max-pooling layers, and two parallel fully connected layers. To adjust the deep network to multitask learning problem, we propose to learn a low-rank deep network so that the relation among different tasks can be explored. We proposed to minimize the number of independent parameter rows of one fully connected layer to explore the relations among different tasks, which is measured by the nuclear norm of the parameter of one fully connected layer, and seek a low-rank parameter matrix. Meanwhile, we also propose to regularize another fully connected layer by sparsity penalty so that the useful features learned by the lower layers can be selected. The learning problem is solved by an iterative algorithm based on gradient descent and back-propagation algorithms. The proposed algorithm is evaluated over benchmark datasets of multiple face attribute prediction, multitask natural language processing, and joint economics index predictions. The evaluation results show the advantage of the low-rank deep CNN model over multitask problems.

Comparative analysis of the diffusion kurtosis imaging and diffusion tensor imaging in grading gliomas, predicting tumour cell proliferation and IDH-1 gene mutation status.

INTRODUCTION: Few studies have applied diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) for the comprehensive assessment of gliomas [tumour grade, isocitrate dehydrogenase-1 (IDH-1) mutation status and tumour proliferation rate (Ki-67)]. This study describes the efficacy of DKI and DTI to comprehensively evaluate gliomas, compares their results. METHODS: Fifty-two patients (18 females; median age, 47.5 years) with pathologically proved gliomas were prospectively included. All cases underwent DKI examination. DKI (mean kurtosis: MK, axial kurtosis: Ka, radial kurtosis: Kr) and DTI (mean diffusivity: MD, fractional anisotropy: FA) maps of each metric was derived. Three ROIs were manually drawn. RESULTS: MK, Ka, Kr and FA were significantly higher in HGGs than in LGGs, whereas MD was significantly lower in HGGs than in LGGs (P < 0.01). ROC analysis demonstrated that MK (specificity: 100% sensitivity: 79%) and Ka (specificity: 96% sensitivity: 82%) had the same and highest (AUC: 0.93) diagnostic value. Moreover, MK, Ka, and Kr were significantly higher in grade III than II gliomas (P ≦ 0.01). Further, DKI and DTI can significantly identify IDH-1 mutation status (P ≦ 0.03). Ka (sensitivity: 74%, specificity: 75%, AUC: 0.72) showed the highest diagnostic value. In addition, DKI metrics and MD showed significant correlations with Ki-67 (P ≦ 0.01) and Ka had the highest correlation coefficient (rs = 0.72). CONCLUSIONS: Compared with DTI, DKI has great advantages for the comprehensive assessment of gliomas. Ka might serve as a promising imaging index in predicting glioma grading, tumour cell proliferation rate and IDH-1 gene mutation status.

Quantitative analysis of neurite orientation dispersion and density imaging in grading gliomas and detecting IDH-1 gene mutation status.

Background and purpose: Neurite orientation dispersion and density imaging (NODDI) is a new diffusion MRI technique that has rarely been applied for glioma grading. The purpose of this study was to quantitatively evaluate the diagnostic efficiency of NODDI in tumour parenchyma (TP) and peritumoural area (PT) for grading gliomas and detecting isocitrate dehydrogenase-1 (IDH-1) mutation status. Methods: Forty-two patients (male: 23, female: 19, mean age: 44.5 y) were recruited and underwent whole brain NODDI examination. Intracellular volume fraction (icvf) and orientation dispersion index (ODI) maps were derived. Three ROIs were manually placed on TP and PT regions for each case. The corresponding average values of icvf and ODI were calculated, and their diagnostic efficiency was assessed. Results: Tumours with high icvfTP (≥0.306) and low icvfPT (≤0.331) were more likely to be high-grade gliomas (HGGs), while lesions with low icvfTP (<0.306) and high icvfPT (>0.331) were prone to be low-grade gliomas (LGGs) (P < 0.001). A multivariate logistic regression model including patient age and icvf values in TP and PT regions most accurately predicted glioma grade (AUC = 0.92, P < 0.001), with a sensitivity and specificity of 92% and 89%, respectively. However, no significant differences were found in NODDI metrics for differentiating IDH-1 mutation status. Conclusions: The quantitative NODDI metrics in the TP and PT regions are highly valuable for glioma grading. A multivariate logistic regression model using the patient age and the icvf values in TP and PT regions showed very high predictive power. However, the utility of NODDI metrics for detecting IDH-1 mutation status has not been fully explored, as a larger sample size may be necessary to uncover benefits.