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A total of 26 elements and volatile organic compounds (VOCs) of Polygonatum cyrtonema in Kaili City (KL), Polygonatum cyrtonema in Leishan County (LS), Polygonatum kingianum in Zhenyuan County (ZY), and Polygonatum sibiricum in Huangping County (HP) were detected and analyzed by microwave digestion, inductively coupled plasma-mass spectrometry (ICP-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), respectively. The differences of inorganic elements and VOCs of the 4 producing areas 3 kinds of Polygonatum spp. were studied by analyzing the content table of inorganic elements, HS-GC-IMS spectrum, principal component analysis (PCA). The result showed that the content of K was the highest among the 3 kinds of Polygonatum spp., followed by Ca, Mg, Fe, Al, Ba, Mn, Zn and Na. The content of these 9 elements in KL, LS, ZY and HP accounted for 99.73%, 99.74%, 99.80% and 99.85% of the total contents of 26 elements measured respectively. There were differences in the quality of the 3 kinds of Polygonatum spp.. Among the samples, the KL had the highest score and the best quality, while the HP had the lowest score. A total of 159 VOCs were detected from 3 kinds of Polygonatum spp., and 101 of them were identified (contains monomers, dimers and trimers). There were mainly aldehydes, alcohols, acids, esters, ketones and other compounds, of which the main substance was hexanal, and the relative content in KL, LS, ZY, and HP accounted for 21.55%, 17.54%, 19.50%, 20.02%, respectively. Ethyl 2-methylpropanoate was higher in KL and LS but not found in ZY. Ethanol, pentanal were higher in ZY and HP, but lower in KL and LS. The difference in the relative content of these substances was the main reason for the difference in the flavors of the 3 kinds of Polygonatum spp.. The research results can provide theoretical and technical support for the development and utilization of Polygonatum spp. resources, the evaluation of flavor characteristics and the classification and identification of varieties in Guizhou Province.

Blood vessel segmentation in fundus images is necessary for the diagnosis of ophthalmic diseases. In recent years, deep learning has achieved eminent performance in blood vessel segmentation, and there still exist challenges to reduce misidentification and improve microvascular segmentation accuracy. One reason is that traditional Convolutional Neural Network (CNN) can not effectively extract multiscale information and discard the unnecessary information. Another reason is we can’t explain why some blood vessels fail to be identified. On the one hand, this paper proposes a Dual Attention Res2UNet (DA-Res2UNet) model. The DA-Res2UNet model uses Res2block rather than CNN to obtain more multiscale information and adds Dual Attention to help the model focus on important information and discard unnecessary information. On the other hand, the explainable method based on a pre-trained fundus image generator is adopted to explore how the model identifies blood vessels. We deduce several special situations that lead to the misidentification based on the model’s explanation and adjust the dataset for these special cases. The adjusted datasets significantly reduce the misidentification in the CHASE_DB1 dataset. Finally, the model trained by the adjusted datasets achieves the state-of-the-art F1-score of 81.88%, 82.77%, and 83.96% on the CHASE_DB1, DRIVE and STARE datasets, respectively.

Abstract Ischemic stroke leads to white matter damage and neurological deficits. However, the characteristics of white matter injury and repair after stroke are unclear. Additionally, the precise molecular communications between microglia and white matter repair during the stroke rehabilitation phase remain elusive. In this current study, MRI DTI scan and immunofluorescence staining were performed to trace white matter and microglia in the mouse transient middle cerebral artery occlusion (tMCAO) stroke model. We found that the most serious white matter damage was on Day 7 after the ischemic stroke, then it recovered gradually from Day 7 to Day 30. Parallel to white matter recovery, we observed that microglia centered around the damaged myelin sheath and swallowed myelin debris in the ischemic areas. Then, microglia of the ischemic hemisphere were sorted by flow cytometry for RNA sequencing and subpopulation analysis. We found that CD11c+ microglia increased from Day 7 to Day 30, demonstrating high phagocytotic capabilities, myelin-supportive genes, and lipid metabolism associated genes. CD11c+ microglia population was partly depleted by the stereotactic injecting of rAAV2/6M-taCasp3 (rAAV2/6M-CMV-DIO-taCasp3-TEVp) into CD11c-cre mice. Selective depletion of CD11c+ microglia disrupted white matter repair, oligodendrocyte maturation, and functional recovery after stroke by Rotarod test, Adhesive Removal test, and Morris Water Maze test. These findings suggest that spontaneous white matter repair occurs after ischemic stroke, while CD11c+ microglia play critical roles in this white matter restorative progress.

Abstract Background Vascular dementia (VAD) is the second most common type of dementia lacking effective treatments. Pentoxifylline (PTX), a nonselective phosphodiesterase inhibitor, displays protective effects in multiple cerebral diseases. In this study, we aimed to investigate the therapeutic effects and potential mechanisms of PTX in VAD. Methods Bilateral common carotid artery stenosis (BCAS) mouse model was established to mimic VAD. Mouse behavior was tested by open field test, novel object recognition test, Y-maze and Morris water maze (MWM) tests. Histological staining, magnetic resonance imaging (MRI) and electron microscopy were used to define white matter integrity. The impact of PTX on microglia phagocytosis, peroxisome proliferator-activated receptors-γ (PPAR-γ) activation and Mer receptor tyrosine kinase (Mertk) expression was assessed by immunofluorescence, western blotting and flow cytometry with the application of microglia-specific Mertk knockout mice, Mertk inhibitor and PPAR-γ inhibitor. Results Here, we found that PTX treatment alleviated cognitive impairment in novel object recognition test, Y-maze and Morris water maze tests. Furthermore, PTX alleviated white matter injury in corpus callosum (CC) and internal capsule (IC) areas as shown by histological staining and MRI analysis. PTX-treatment group presented thicker myelin sheath than vehicle group by electron microscopy. Mechanistically, PTX facilitated microglial phagocytosis of myelin debris by up-regulating the expression of Mertk in BCAS model and primary cultured microglia. Importantly, microglia-specific Mertk knockout blocked the therapeutic effects of PTX in BCAS model. Moreover, Mertk expression was regulated by the nuclear translocation of PPAR-γ. Through modulating PPAR-γ, PTX enhanced Mertk expression. Conclusions Collectively, our results demonstrated that PTX showed therapeutic potentials in VAD and alleviated ischemic white matter injury via modulating Mertk-mediated myelin clearance in microglia.

ObjectiveChemotherapy-related brain impairments and changes can occur in patients with lung cancer after platinum chemotherapy and have a substantial impact on survivors’ quality of life. Therefore, it is necessary to understand the brain neuropathological alterations and response mechanisms to provide a theoretical basis for rehabilitation strategies. This study aimed to investigate the related brain morphological changes and clarified their correlation with clinical and pathological indicators in patients with lung cancer after platinum chemotherapy.MethodsOverall, 28 patients with chemotherapy, 56 patients without chemotherapy, and 41 healthy controls were categorized in three groups, matched for age, sex, and years of education, and included in the cross-sectional comparison of brain volume and cortical thickness. 14 matched patients before and after chemotherapy were subjected to paired comparison for longitudinal observation of brain morphological changes. Three-dimensional T1-weighted images were acquired from all participants, and quantitative parameters were calculated using the formula of the change from baseline. Correlation analysis was performed to evaluate the relationship between abnormal morphological indices and clinical information of patients.ResultsBrain regions with volume differences among the three groups were mainly distributed in frontal lobe and limbic cortex. Additionally, significant differences in cerebrospinal fluid were observed in most ventricles, and the main brain regions with cortical thickness differences were the gyrus rectus and medial frontal cortex of the frontal lobe, transverse temporal gyrus of the temporal lobe, insular cortex, anterior insula, and posterior insula of the insular cortex. According to the paired comparison, decreased brain volumes in the patients after chemotherapy appeared in some regions of the frontal, parietal, temporal, and occipital lobes; limbic cortex; insular cortex; and lobules VI-X and decreased cortical thickness in the patients after chemotherapy was found in the frontal, temporal, limbic, and insular cortexes. In the correlation analysis, only the differentiation degree of the tumor and duration after chemotherapy were significantly correlated with imaging indices in the abnormal brain regions.ConclusionsOur findings illustrate the platinum-related brain reactivity morphological alterations which provide more insights into the neuropathological mechanisms of patients with lung cancer after platinum chemotherapy and empirical support for the details of brain injury related to cancer and chemotherapy.

ObjectiveTo evaluate the feasibility of 9. 4-T postmortem MRI (pm-MRI) for assessment of major congenital heart defects (CHD) cases terminated in the early stage of gestation.MethodsFetuses with CHD detected by the detailed first-trimester ultrasound scan and terminated before 18 gestational weeks were recruited between January 2018 and June 2020. All fetuses were offered 9.4-T pm-MRI examinations and those terminated over 13+6 weeks were offered conventional autopsies simultaneously. Findings of pm-MRI were compared with those of conventional autopsy and prenatal ultrasound.ResultsA total of 19 fetuses with major CHD were analyzed, including 6 cases of the atrioventricular septal defect, 5 cases of Tetralogy of Fallot, 3 cases of hypoplastic left heart syndrome, 1 case of tricuspid atresia, 1 case of transposition of the great arteries, 1 case of severe tricuspid regurgitation, and 2 cases of complex CHD. Pm-MRI had concordant findings in 73.7% (14/19) cases, discordant findings in 15.8% (3/19) cases, and additional findings in 10.5% (2/19) cases when compared with prenatal ultrasound. Pm-MRI findings were concordant with autopsy in all 8 CHD cases terminated over 13+6 weeks.ConclusionIt is feasible to exhibit the structure of fetal heart terminated in the first trimester clearly on 9.4-T pm-MRI with an optimized scanning protocol. High-field pm-MRI could provide medical imaging information of CHD for those terminated in the early stage of gestation, especially for those limited by conventional autopsy.

Both episodic memory and executive function are impaired in amnestic mild cognitive impairment (aMCI) subjects, but it is unclear if these impairments are independent or interactive. The present study aimed to explore the relationship between episodic memory deficits and executive function deficits, and the underlying functional mechanisms in aMCI subjects. Thirty-one aMCI subjects and 27 healthy subjects underwent neuropsychological tests and multimodal magnetic resonance imaging (MRI) scans. Hippocampal networks and medial prefrontal cortex (MPFC) networks were identified based on resting-sate functional MRI (fMRI) data. AMCI subjects displayed lower episodic memory scores and executive function scores than control subjects, and the episodic memory scores were positively correlated with the executive function scores in aMCI subjects. Brain network analyses showed an interaction between the hippocampal networks and the MPFC networks, and the interaction was significantly associated with the episodic memory scores and the executive function scores. Notably, aMCI subjects displayed higher functional connectivity (FC) of the right hippocampal network with the right prefrontal cortex than did control subjects, but this difference disappeared when controlling for the MPFC networks. Furthermore, the effects of the MPFC networks on the hippocampal networks were significantly associated with the episodic memory scores in aMCI subjects. The present findings suggested that the episodic memory deficits in aMCI subjects could be partially underpinned by the modulation of the MPFC networks on the hippocampal networks.

Frontotemporal dementia (FTD) and Alzheimer’s disease (AD) have overlapping symptoms, and accurate differential diagnosis is important for targeted intervention and treatment. Previous studies suggest that the deep learning (DL) techniques have the potential to solve the differential diagnosis problem of FTD, AD and normal controls (NCs), but its performance is still unclear. In addition, existing DL-assisted diagnostic studies still rely on hypothesis-based expert-level preprocessing. On the one hand, it imposes high requirements on clinicians and data themselves; On the other hand, it hinders the backtracking of classification results to the original image data, resulting in the classification results cannot be interpreted intuitively. In the current study, a large cohort of 3D T1-weighted structural magnetic resonance imaging (MRI) volumes (n = 4,099) was collected from two publicly available databases, i.e., the ADNI and the NIFD. We trained a DL-based network directly based on raw T1 images to classify FTD, AD and corresponding NCs. And we evaluated the convergence speed, differential diagnosis ability, robustness and generalizability under nine scenarios. The proposed network yielded an accuracy of 91.83% based on the most common T1-weighted sequence [magnetization-prepared rapid acquisition with gradient echo (MPRAGE)]. The knowledge learned by the DL network through multiple classification tasks can also be used to solve subproblems, and the knowledge is generalizable and not limited to a specified dataset. Furthermore, we applied a gradient visualization algorithm based on guided backpropagation to calculate the contribution graph, which tells us intuitively why the DL-based networks make each decision. The regions making valuable contributions to FTD were more widespread in the right frontal white matter regions, while the left temporal, bilateral inferior frontal and parahippocampal regions were contributors to the classification of AD. Our results demonstrated that DL-based networks have the ability to solve the enigma of differential diagnosis of diseases without any hypothesis-based preprocessing. Moreover, they may mine the potential patterns that may be different from human clinicians, which may provide new insight into the understanding of FTD and AD.

Background: The degenerative pattern of white matter (WM) microstructures during Alzheimer's disease (AD) and its relationship with cognitive function have not yet been clarified. The present research aimed to explore the alterations of the WM microstructure and its impact on amnestic mild cognitive (aMCI) and AD patients. Mechanical learning methods were used to explore the validity of WM microstructure lesions on the classification in AD spectrum disease.Methods: Neuropsychological data and diffusion tensor imaging (DTI) images were collected from 28 AD subjects, 31 aMCI subjects, and 27 normal controls (NC). Tract-based spatial statistics (TBSS) were used to extract diffusion parameters in WM tracts. We performed ANOVA analysis to compare diffusion parameters and clinical features among the three groups. Partial correlation analysis was used to explore the relationship between diffusion metrics and cognitive functions controlling for age, gender, and years of education. Additionally, we performed the support vector machine (SVM) classification to determine the discriminative ability of DTI metrics in the differentiation of aMCI and AD patients from controls.Results: As compared to controls or aMCI patients, AD patients displayed widespread WM lesions, including in the inferior longitudinal fasciculus, inferior fronto-occipital fasciculi, and superior longitudinal fasciculus. Significant correlations between fractional anisotropy (FA), mean diffusivity (MD), and radial diffusion (RD) of the long longitudinal tract and memory deficits were found in aMCI and AD groups, respectively. Furthermore, through SVM classification, we found DTI indicators generated by FA and MD parameters can effectively distinguish AD patients from the control group with accuracy rates of up to 89 and 85%, respectively.Conclusion: The WM microstructure is extensively disrupted in AD patients, and the WM integrity of the long longitudinal tract is closely related to memory, which would hold potential value for monitoring the progression of AD. The method of classification based on SVM and WM damage features may be objectively helpful to the classification of AD diseases.

Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.

Background and Objective: Subjective cognitive decline (SCD) is considered a preclinical state of Alzheimer’s disease (AD) and may represent a more advanced preclinical status than amnestic mild cognitive impairment (aMCI). Our aim was to explore changes in the white matter (WM) microstructure and their correlation with cognitive function in these AD-spectrum patients.Methods: Diffusion tensor images from 43 individuals with normal cognition (NC), 38 SCD patients, and 36 aMCI patients were compared using an atlas-based segmentation strategy. The correlation between diffusion parameters and cognitive function was further analyzed.Results: The anatomical pattern of WM impairment was generally similar between SCD and aMCI patients. However, aMCI patients showed significantly lower fractional anisotropy (i.e., corpus callosum forceps major and forceps minor) and increased mean diffusivity [i.e., bilateral anterior thalamic radiation (ATR), left corticospinal tract (CST), forceps minor, left cingulum (cingulate gyrus), left cingulum hippocampus, and left inferior fronto-occipital fasciculus (IFO)] in some tracts than did SCD subjects, indicating a disruption in WM microstructural integrity in the aMCI. Individuals with microstructural disruption in forceps minor, left cingulum (cingulate gyrus), and left cingulum hippocampus tracts performed worse in general cognition and memory function tests, as indicated by line regression analysis.Conclusion: SCD individuals had extensive WM microstructural damage in a pattern similar to that seen in aMCI, although presenting a cognitive performance comparable with that of cognitively healthy individuals. Our results suggest that WM integrity might precede objectively measurable memory decline and may be a potential early biomarker for AD.

ObjectiveWhite matter hyperintensities (WMH) is an important cause of vascular cognitive impairment (CI). However, a considerable portion of individuals with WMH do not develop CI. The present study aimed to investigate distinctive regional brain activity and connectivity patterns in WMH subjects with and without CI, who displayed comparable WMH burden.MethodsFourteen WMH subjects with CI, 16 WMH subjects without CI and 37 healthy subjects underwent multimodal MRI scans and neuropsychological tests. All WMH subjects displayed Fazekas grade 2 of WMH. Regional Homogeneity (ReHo) and functional connectivity (FC) patterns were identified based on resting-state functional MRI data.ResultsNo significant differences in WMH volume, the number of WMH lesions and brain volume were shown between the 2 WMH groups. In contrast, the WMH with CI group showed higher ReHo in bilateral superior parietal gyrus (SPG)/superior occipital gyrus (SOG) than the WMH without CI group. Compared with the WMH without CI group, the WMH with CI group also displayed higher FC of the left SPG/SOG with frontal regions, and higher FC of the right SPG/SOG with parietal regions. Furthermore, higher FC of the left SPG/SOG with frontal regions were significantly associated with less worse executive dysfunction in WMH with CI subjects, suggesting a compensatory effect.ConclusionHigher local coherence of activities in the SPG/SOG and higher connectivity of the SPG/SOG with parietal and frontal regions are related to CI in WMH subjects. The findings provide novel insights into functional alterations underlying the cognitive variety in WMH subjects.

Background: Cerebral small vessel disease (SVD) is a common cause of cognitive dysfunction. However, little is known whether the altered reconfiguration pattern of brain modular architecture regulates cognitive dysfunction in SVD.Methods: We recruited 25 cases of SVD without cognitive impairment (SVD-NCI) and 24 cases of SVD with mild cognitive impairment (SVD-MCI). According to the Framingham Stroke Risk Profile, healthy controls (HC) were divided into 17 subjects (HC-low risk) and 19 subjects (HC-high risk). All individuals underwent resting-state functional magnetic resonance imaging and cognitive assessments. Graph-theoretical analysis was used to explore alterations in the modular organization of functional brain networks. Multiple regression and mediation analyses were performed to investigate the relationship between MRI markers, network metrics and cognitive performance.Results: We identified four modules corresponding to the default mode network (DMN), executive control network (ECN), sensorimotor network and visual network. With increasing vascular risk factors, the inter- and intranetwork compensation of the ECN and a relatively reserved DMN itself were observed in individuals at high risk for SVD. With declining cognitive ability, SVD-MCI showed a disrupted ECN intranetwork and increased DMN connection. Furthermore, the intermodule connectivity of the right inferior frontal gyrus of the ECN mediated the relationship between periventricular white matter hyperintensities and visuospatial processing in SVD-MCI.Conclusions: The reconfiguration pattern of the modular architecture within/between the DMN and ECN advances our understanding of the neural underpinning in response to vascular risk and SVD burden. These observations may provide novel insight into the underlying neural mechanism of SVD-related cognitive impairment and may serve as a potential non-invasive biomarker to predict and monitor disease progression.

Brain white matter fiber bundles in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) have abnormalities not usually seen in unaffected subjects. Ideal algorithm of the localization-specific properties in white matter integrity might reveal the changes of tissue properties varying along each tract, while previous studies only detected the mean DTI parameters of each fiber. The aim of this study was to investigate whether these abnormalities of nerve fiber tracts are localized to specific regions of the tracts or spread throughout and to analyze which of the examined fiber tracts are involved in the early stages of Alzheimer's disease. In this study, we utilized VBA, TBSS as well as AFQ together to comprehensively investigate the white matter fiber impairment on 25 CE patients, 29 MCI patients and 34 normal control (NC) subjects. Two tract profiles, fractional anisotropy (FA) and mean diffusivity (MD), were extracted to evaluate the white matter integrity at 100 locations along each of 20 fiber tracts and then we validated the results with 27 CE patients, 21 MCI patients and 22 NC from the ADNI cohort. Also, we compare the AFQ with VBA and TBSS in our cohort. In comparison with NC, AD patients showed widespread FA reduction in 25% (5 /20) and MD increase in 65%(13/20) of the examined fiber tracts. The MCI patients showed a regional FA reduction in 5% (1/20) of the examined fiber tracts (right cingulum cingulate) and MD increase in 5%(1/20) of the examined fiber tracts (left arcuate fasciculus). Among these changed tracts, only the right cingulum cingulate showed widespread disruption of myelin or/and fiber axons in MCI and aggravated deterioration in AD, findings supported by FA/MD changes both by the mean and FA changes by point wise methods and TBSS. And the AFQ findings from ADNI cohort showed some similarity with our cohort, especially in the pointwise comparison of MD profiles between AD vs NC. Furthermore, the pattern of white matter abnormalities was different across neuronal fiber tracts; for example, the MCI and AD patients showed similar FA reduction in the middle part of the right cingulum cingulate, and the anterior part were not damaged. However, the left arcuate fasciculus showed MD elevation located at the temporal part of the fibers in the MCI patients and expanding to the temporal and middle part of the fibers in AD patients. So, the AFQ may be an alternative complementary method of VBA and TBSS, and may provide new insights into white matter degeneration in MCI and its association with AD. Keywords: Alzheimer's disease, Mild cognitive impairment, Automated fiber quantification, Diffusion tensor imaging, Pointwise comparison

Deep gray matter structures are associated with memory and other important functions that are impaired in Alzheimer’s disease (AD) and mild cognitive impairment (MCI). However, systematic characterization of the subregional atrophy and deformations in these structures in AD and MCI still need more investigations. In this article, we combined complex volumetry- and vertex-based analysis to investigate the pattern of subregional structural alterations in deep gray matter structures and its association with global clinical scores in AD (n = 30) and MCI patients (n = 30), compared to normal controls (NCs, n = 30). Among all seven pairs of structures, the bilateral hippocampi and nucleus accumbens showed significant atrophy in AD compared with NCs (p 0.05). In conclusion, the atrophy of these four subregions in bilateral hippocampi and nucleus accumbens was associated with cognitive impairment of patients, which might be potential target regions of treatment in AD. The surface analysis could provide additional information to volume comparison in finding the early pathological progress in deep gray matter structures.

Impairment of spatial navigation (SN) skills is one of the features of the Alzheimer’s disease (AD) already at the stage of mild cognitive impairment (MCI). We used a computer-based battery of spatial navigation tests to measure the SN performance in 22 MCI patients as well as 21 normal controls (NC). In order to evaluate intrinsic activity in the subcortical regions that may play a role in SN, we measured ALFF, fALFF, and ReHo derived within 14 subcortical regions. We observed reductions of intrinsic activity in MCI patients. We also demonstrated that the MCI versus NC group difference can modulate activity-behavior relationship, that is, the correlation slopes between ReHo and allocentric SN task total errors were significantly different between NC and MCI groups in the right hippocampus (interaction F=4.44, p=0.05), pallidum (F=8.97, p=0.005), and thalamus (F=5.95, p=0.02), which were negative in NC (right hippocampus, r=−0.49; right pallidum, r=−0.50; right thalamus, r=−0.45; all p0.2). These findings may provide a novel insight of the brain mechanism associated with SN impairment in MCI and indicated a stage specificity of brain-behavior correlation in dementia. This trial is registered with ChiCTR-BRC-17011316.

Background. Generally, males display greater strength and muscle capacity than females while performing a task. Muscle biopsy is regarded as the reference method of evaluating muscle functions; however, it is invasive and has sampling errors, and is not practical for longitudinal studies and dynamic measurement during excise. In this study, we built an in-house force control and gauge system for quantitatively applying force to quadriceps while the subjects underwent 31P Magnetic Resonance Spectroscopy (31P-MRS); our aim was to investigate if there is a sex difference of phosphate metabolite change in working muscles in young heathy Chinese volunteers. Methods. Volunteers performed knee-extending excises using a force control and gauge system while lying prone in a Philips 3T Magnetic Resonance (MR) scanner. The 31P-MRS coil was firmly placed under the middle of the quadriceps . 31P-MRS measurements of inorganic phosphate (Pi), phosphocreatine (PCr) and adenosine triphosphate (ATP) were acquired from quadriceps while subjects were in a state of pre-, during- and post-exercise. The PCr, Pi, PCr/Pi, PCr/ATP, pH, work/energy cost ratio (WE), kPCr and oxidative capacity were compared between males and females. Results. A total of 17 volunteers underwent the study. Males: N = 10, age = 23.30 ± 1.25years; females: N = 7, age = 23.57 ± 0.79 years. In this study, males had significantly greater WE (16.33 ± 6.46 vs. 7.82 ± 2.16, p = 0.002) than females. Among PCr, Pi, PCr/Pi, PCr/ATP, pH, kPCr and oxidative capacity at different exercise status, only PCr/Pi (during-exercise, males = 5.630 ± 1.647, females = 4.014 ± 1.298, p = 0.047), PCr/ATP (during-exercise, males =1.273 ± 0.219, females = 1.523 ± 0.167, p = 0.025), and ATP (post-exercise, males = 24.469 ± 3.911 mmol/kg, females = 18.353 ± 4.818 mmol/kg, p = 0.035) had significant sex differences. Males had significantly greater PCr/Pi, but less PCr/ATP than females during exercise, suggesting males had higher energy transfer efficiency than females. At the post-exercise status, the recovery of PCr did not show sex difference. Conclusions. Our in-house force control and gauge system quantitatively applied force during the exercise for 31P-MRS experiments, and a sex difference of higher energy transfer efficiency and WE was detected in males with mild loaded exercising quadriceps. This noninvasive technology allows us to further study and understand the sex difference of high energy phosphate metabolism in the future.

[This corrects the article DOI: 10.1371/journal.pone.0153369.].

Many modalities of magnetic resonance imaging (MRI) have been confirmed to be of great diagnostic value in glioma grading. Contrast enhanced T1-weighted imaging allows the recognition of blood-brain barrier breakdown. Perfusion weighted imaging and MR spectroscopic imaging enable the quantitative measurement of perfusion parameters and metabolic alterations respectively. These modalities can potentially improve the grading process in glioma if combined properly. In this study, Bayesian Network, which is a powerful and flexible method for probabilistic analysis under uncertainty, is used to combine features extracted from contrast enhanced T1-weighted imaging, perfusion weighted imaging and MR spectroscopic imaging. The networks were constructed using K2 algorithm along with manual determination and distribution parameters learned using maximum likelihood estimation. The grading performance was evaluated in a leave-one-out analysis, achieving an overall grading accuracy of 92.86% and an area under the curve of 0.9577 in the receiver operating characteristic analysis given all available features observed in the total 56 patients. Results and discussions show that Bayesian Network is promising in combining features from multiple modalities of MRI for improved grading performance.

Purpose. To examine the associations among age, Apolipoprotein E (APOE) genotype, metabolic changes in the hippocampus detected by 2D 1H magnetic resonance spectroscopy (MRS), and neuropsychological measures of cognition in non-demented elders.Materials and Methods. We studied a cohort of 16 cognitively normal controls (CN) and 11 amnestic mild cognitive impairment (aMCI) patients between 66 and 88 years old who were genotyped for APOE genetic polymorphism. Measurements of 2D1H-MRS metabolites were obtained in the hippocampus region. Adjusting by age among all subjects, the association between metabolic changes and cognitive function was measured by Spearman partial rank-order correlation. The effect of APOE status was measured by separating the subjects into APOE genotype subgroups, including the APOEε4 carriers and APOEε4 non-carriers.Results. In contrast to the CN group matched with age, gender, and education, aMCI patients showed increased myo-inositol (mI)/Creatine (Cr) ratio only in the right hippocampus. No differences were noted on N-acetylaspartate (NAA)/Cr and mI/NAA from bilateral hippocampus, and so was mI/Cr ratio in left hippocampus between aMCI and CN. The mI/Cr ratio from the right hippocampus in non-demented elders was negatively correlated with Montreal Cognitive Assessment (MoCA) scores. Whether ε4 genotype or age was added as a covariate, none of the correlation effects remained significant. Additionally, adjusting for age and APOE genotype together, there was no significant correlation between them.Conclusion. Since the higher mI/Cr from the right hippocampus of the patients with aMCI than those from CN, the mI/Cr could be a more specific predictor of general cognitive function in aMCI patients. There is an association between higher mI/Cr in right hippocampus and worse cognitive function for the non-demented older adults, and the correlation could be modified by APOE status and age. That provided a window on objectively understanding the mechanism between the brain metabolites and the influence factors in non-demented elders.