Loss of p53 drives neuron reprogramming in head and neck cancer.

The solid tumour microenvironment includes nerve fibres that arise from the peripheral nervous system1,2. Recent work indicates that newly formed adrenergic nerve fibres promote tumour growth, but the origin of these nerves and the mechanism of their inception are unknown1,3. Here, by comparing the transcriptomes of cancer-associated trigeminal sensory neurons with those of endogenous neurons in mouse models of oral cancer, we identified an adrenergic differentiation signature. We show that loss of TP53 leads to adrenergic transdifferentiation of tumour-associated sensory nerves through loss of the microRNA miR-34a. Tumour growth was inhibited by sensory denervation or pharmacological blockade of adrenergic receptors, but not by chemical sympathectomy of pre-existing adrenergic nerves. A retrospective analysis of samples from oral cancer revealed that p53 status was associated with nerve density, which was in turn associated with poor clinical outcomes. This crosstalk between cancer cells and neurons represents mechanism by which tumour-associated neurons are reprogrammed towards an adrenergic phenotype that can stimulate tumour progression, and is a potential target for anticancer therapy.

Relationship Between Microstructural Alterations and Cognitive Decline After Whole-Brain Radiation Therapy for Brain Metastases: An Exploratory Whole-Brain MR Analysis Based on Neurite Orientation Dispersion and Density Imaging.

BACKGROUND: Cognitive impairment frequently occurs in patients with brain metastases (BM) after whole-brain radiotherapy (WBRT). It is crucial to explore the underlying mechanisms of cognitive impairment in BM patients receiving WBRT. PURPOSE: To detect brain microstructural alterations in patients after WBRT by neurite orientation dispersion and density imaging (NODDI), and evaluate the performance of microstructural alterations in predicting cognitive impairment. STUDY TYPE: Prospective. POPULATION: Twenty-six patients (seven female; mean age, 60.9 years). FIELD STRENGTH/SEQUENCE: 3-T, multi-shell diffusion-weighted single-shot echo-planar sequence. Three-dimensional magnetization-prepared rapid acquisition with gradient echo sequence. ASSESSMENT: Mini-mental state examination (MMSE) evaluations were conducted prior to, following, 1 and 3 months after WBRT. The diffusion data were collected twice, 1 week before and 1 week after WBRT. NODDI analysis was conducted to assess microstructural alterations in whole brain (orientation dispersion index, neurite density index, volume fraction of isotropic water molecules). Reliable change indices (RCI) of MMSE were used to measure cognitive decline. The performance of support vector machine models based on NODDI parameters and clinical features (prednisone usage, tumor volume, etc.) in predicting MMSE-RCI was evaluated. STATISTICAL TESTS: Paired t-test to assess alterations of NODDI measures and MMSE during follow-up. Statistical significance level of P-value <0.05. RESULTS: Significantly decreased MMSE score was found at 3 months after WBRT. After WBRT, corpus callosum, medial prefrontal cortex, limbic lobe, occipital lobe, parietal lobe, putamen, globus pallidus lentiform, and thalamus demonstrated damage in NODDI parameters. The predicted MMSE-RCI based on NODDI features was significantly associated with the measured MMSE-RCI at 1 month (R = 0.573; P = 0.003) and 3 months (R = 0.687; P < 0.0001) after WBRT. DATA CONCLUSION: Microstructural alterations in several brain regions including the middle prefrontal and limbic cortexes were observed in patients with BM following WBRT, which may contribute to subsequent cognitive decline. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Neurite outgrowth deficits caused by rare PLXNB1 mutation in pediatric bipolar disorder.

Pediatric bipolar disorder (PBD) is a severe mood dysregulation condition that affects 0.5-1% of children and teens in the United States. It is associated with recurrent episodes of mania and depression and an increased risk of suicidality. However, the genetics and neuropathology of PBD are largely unknown. Here, we used a combinatorial family-based approach to characterize cellular, molecular, genetic, and network-level deficits associated with PBD. We recruited a PBD patient and three unaffected family members from a family with a history of psychiatric illnesses. Using resting-state functional magnetic resonance imaging (rs-fMRI), we detected altered resting-state functional connectivity in the patient as compared to an unaffected sibling. Using transcriptomic profiling of patient and control induced pluripotent stem cell (iPSC)-derived telencephalic organoids, we found aberrant signaling in the molecular pathways related to neurite outgrowth. We corroborated the presence of neurite outgrowth deficits in patient iPSC-derived cortical neurons and identified a rare homozygous loss-of-function PLXNB1 variant (c.1360C>C; p.Ser454Arg) responsible for the deficits in the patient. Expression of wild-type PLXNB1, but not the variant, rescued neurite outgrowth in patient neurons, and expression of the variant caused the neurite outgrowth deficits in cortical neurons from PlxnB1 knockout mice. These results indicate that dysregulated PLXNB1 signaling may contribute to an increased risk of PBD and other mood dysregulation-related disorders by disrupting neurite outgrowth and functional brain connectivity. Overall, this study established and validated a novel family-based combinatorial approach for studying cellular and molecular deficits in psychiatric disorders and identified dysfunctional PLXNB1 signaling and neurite outgrowth as potential risk factors for PBD.

High-performance presurgical differentiation of glioblastoma and metastasis by means of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics.

OBJECTIVES: To evaluate the performance of multiparametric neurite orientation dispersion and density imaging (NODDI) radiomics in distinguishing between glioblastoma (Gb) and solitary brain metastasis (SBM). MATERIALS AND METHODS: In this retrospective study, NODDI images were curated from 109 patients with Gb (n = 57) or SBM (n = 52). Automatically segmented multiple volumes of interest (VOIs) encompassed the main tumor regions, including necrosis, solid tumor, and peritumoral edema. Radiomics features were extracted for each main tumor region, using three NODDI parameter maps. Radiomics models were developed based on these three NODDI parameter maps and their amalgamation to differentiate between Gb and SBM. Additionally, radiomics models were constructed based on morphological magnetic resonance imaging (MRI) and diffusion imaging (diffusion-weighted imaging [DWI]; diffusion tensor imaging [DTI]) for performance comparison. RESULTS: The validation dataset results revealed that the performance of a single NODDI parameter map model was inferior to that of the combined NODDI model. In the necrotic regions, the combined NODDI radiomics model exhibited less than ideal discriminative capabilities (area under the receiver operating characteristic curve [AUC] = 0.701). For peritumoral edema regions, the combined NODDI radiomics model achieved a moderate level of discrimination (AUC = 0.820). Within the solid tumor regions, the combined NODDI radiomics model demonstrated superior performance (AUC = 0.904), surpassing the models of other VOIs. The comparison results demonstrated that the NODDI model was better than the DWI and DTI models, while those of the morphological MRI and NODDI models were similar. CONCLUSION: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM. CLINICAL RELEVANCE STATEMENT: The NODDI radiomics model showed promising performance for preoperative discrimination between Gb and SBM, and radiomics features can be incorporated into the multidimensional phenotypic features that describe tumor heterogeneity. KEY POINTS: • The neurite orientation dispersion and density imaging (NODDI) radiomics model showed promising performance for preoperative discrimination between glioblastoma and solitary brain metastasis. • Compared with other tumor volumes of interest, the NODDI radiomics model based on solid tumor regions performed best in distinguishing the two types of tumors. • The performance of the single-parameter NODDI model was inferior to that of the combined-parameter NODDI model.

Mapping frontoinsular cortex from diffusion microstructure.

We developed a novel method for mapping the location, surface area, thickness, and volume of frontoinsular cortex (FI) using structural and diffusion magnetic resonance imaging. FI lies in the ventral part of anterior insular cortex and is characterized by its distinctive population von Economo neurons (VENs). Functional neuroimaging studies have revealed its involvement in affective processing, and histopathology has implicated VEN loss in behavioral-variant frontotemporal dementia and chronic alcoholism; however, structural neuroimaging of FI has been relatively limited. We delineated FI by jointly modeling cortical surface geometry and its coincident diffusion microstructure parameters. We found that neurite orientation dispersion in cortical gray matter can be used to map FI in specific individuals, and the derived measures reflect a range of behavioral factors in young adults from the Human Connectome Project (N=1052). FI volume was larger in the left hemisphere than the right (31%), and the percentage volume of FI was larger in women than men (15.3%). FI volume was associated with measures of decision-making (delay discounting, substance abuse), emotion (negative intrusive thinking and perception of hostility), and social behavior (theory of mind and working memory for faces). The common denominator is that larger FI size is related to greater self-control and social awareness.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study.

BACKGROUND: New daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH. METHODS: This study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson's correlation analysis between the NODDI indicators and clinical characteristics. RESULTS: Compared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction. CONCLUSIONS: Our research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

Glutathione S-transferase Pi (Gstp) proteins regulate neuritogenesis in the developing cerebral cortex.

GSTP proteins are metabolic enzymes involved in the removal of oxidative stress and intracellular signaling and also have inhibitory effects on JNK activity. However, the functions of Gstp proteins in the developing brain are unknown. In mice, there are three Gstp proteins, Gstp1, 2 and 3, whereas there is only one GSTP in humans. By reverse transcription-polymerase chain reaction (RT-PCR) analysis, we found that Gstp1 was expressed beginning at E15.5 in the cortex, but Gstp2 and 3 started expressing at E18.5. Gstp 1 and 2 knockdown (KD) caused decreased neurite number in cortical neurons, implicating them in neurite initiation. Using in utero electroporation (IUE) to knock down Gstp1 and 2 in layer 2/3 pyramidal neurons in vivo, we found abnormal swelling of the apical dendrite at P3 and reduced neurite number at P15. Using time-lapse live imaging, we found that the apical dendrite orientation was skewed compared with the control. We explored the molecular mechanism and found that JNK inhibition rescued reduced neurite number caused by Gstp knockdown, indicating that Gstp regulates neurite formation through JNK signaling. Thus, we found novel functions of Gstp proteins in neurite initiation during cortical development. These findings not only provide novel functions of Gstp proteins in neuritogenesis during cortical development but also help us to understand the complexity of neurite formation.

Cortical plasticity in central vision loss: Cortical thickness and neurite structure.

Late-stage macular degeneration (MD) often causes retinal lesions depriving an individual of central vision, forcing them to learn to use peripheral vision for daily tasks. To compensate, many patients develop a preferred retinal locus (PRL), an area of peripheral vision used more often than equivalent regions of spared vision. Thus, associated portions of cortex experience increased use, while portions of cortex associated with the lesion are deprived of sensory input. Prior research has not well examined the degree to which structural plasticity depends on the amount of use across the visual field. Cortical thickness, neurite density, and orientation dispersion were measured at portions of cortex associated with the PRL, the retinal lesion, and a control region in participants with MD as well as age-matched, gender-matched, and education-matched controls. MD participants had significantly thinner cortex in both the cortical representation of the PRL (cPRL) and the control region, compared with controls, but no significant differences in thickness, neurite density, or orientation dispersion were found between the cPRL and the control region as functions of disease or onset. This decrease in thickness is driven by a subset of early-onset participants whose patterns of thickness, neurite density, and neurite orientation dispersion are distinct from matched control participants. These results suggest that people who develop MD earlier in adulthood may undergo more structural plasticity than those who develop it late in life.

Mapping the macrostructure and microstructure of the in vivo human hippocampus using diffusion MRI.

The hippocampus is classically divided into mesoscopic subfields which contain varying microstructure that contribute to their unique functional roles. It has been challenging to characterize this microstructure with current magnetic resonance based neuroimaging techniques. In this work, we used diffusion magnetic resonance imaging (dMRI) and a novel surface-based approach in the hippocampus which revealed distinct microstructural distributions of neurite density and dispersion, T1w/T2w ratio as a proxy for myelin content, fractional anisotropy, and mean diffusivity. We used the neurite orientation dispersion and density imaging (NODDI) model optimized for grey matter diffusivity to characterize neurite density and dispersion. We found that neurite dispersion was highest in the cornu ammonis (CA) 1 and subiculum subfields which likely captures the large heterogeneity of tangential and radial fibres, such as the Schaffer collaterals, perforant path, and pyramidal neurons. Neurite density and T1w/T2w were highest in the subiculum and CA3 and lowest in CA1, which may reflect known myeloarchitectonic differences between these subfields. Using a simple logistic regression model, we showed that neurite density, dispersion, and T1w/T2w measures were separable across the subfields, suggesting that they may be sensitive to the known variability in subfield cyto- and myeloarchitecture. We report macrostructural measures of gyrification, thickness, and curvature that were in line with ex vivo descriptions of hippocampal anatomy. We employed a multivariate orthogonal projective non-negative matrix factorization (OPNNMF) approach to capture co-varying regions of macro- and microstructure across the hippocampus. The clusters were highly variable along the medial-lateral (proximal-distal) direction, likely reflecting known differences in morphology, cytoarchitectonic profiles, and connectivity. Finally, we show that by examining the main direction of diffusion relative to canonical hippocampal axes, we could identify regions with stereotyped microstructural orientations that may map onto specific fibre pathways, such as the Schaffer collaterals, perforant path, fimbria, and alveus. These results highlight the value of combining in vivo dMRI with computational approaches for capturing hippocampal microstructure, which may provide useful features for understanding cognition and for diagnosis of disease states.

Both noise-floor and tissue compartment difference in diffusivity contribute to FA dependence on b-value in diffusion MRI.

Noninvasive diffusion magnetic resonance imaging (dMRI) has been widely employed in both clinical and research settings to investigate brain tissue microstructure. Despite the evidence that dMRI-derived fractional anisotropy (FA) correlates with white matter properties, the metric is not specific. Recent studies have reported that FA is dependent on the b-value, and its origin has primarily been attributed to either the influence of microstructure or the noise-floor effect. A systematic investigation into the inter-relationship of these two effects is however still lacking. This study aims to quantify contributions of the reported differences in intra- and extra-neurite diffusivity to the observed changes in FA, in addition to the noise in measurements. We used in-vivo and post-mortem human brain imaging, as well as numerical simulations and histological validation, for this purpose. Our investigations reveal that the percentage difference of FA between b-values (pdFA) has significant positive associations with neurite density index (NDI), which is derived from in-vivo neurite orientation dispersion and density imaging (NODDI), or Bielschowsky's silver impregnation (BIEL) staining sections of fixed post-mortem human brain samples. Furthermore, such an association is found to be varied with Signal-to-Noise Ratio (SNR) level, indicating a nonlinear interaction effect between tissue microstructure and noise. Finally, a multicompartment model simulation revealed that these findings can be driven by differing diffusivities of intra- and extra-neurite compartments in tissue, with the noise-floor further amplifying the effect. In conclusion, both the differences in intra- and extra-neurite diffusivity and noise-floor effects significantly contribute to the FA difference associated with the b-value.

Integrating multimodality magnetic resonance imaging to the Allen Mouse Brain Common Coordinate Framework.

High-resolution magnetic resonance imaging (MRI) affords unique image contrasts to nondestructively probe the tissue microstructure; validation of MRI findings with conventional histology is essential to better understand the MRI contrasts. However, the dramatic difference in the spatial resolution and image contrast of these two techniques impedes accurate comparison between MRI metrics and traditional histology. To better validate various MRI metrics, we acquired whole mouse brain multigradient recalled-echo and multishell diffusion MRI datasets at 25-µm isotropic resolution. The recently developed Allen Mouse Brain Common Coordinate Framework (CCFv3) provides opportunities to integrate multimodal and multiscale datasets of the whole mouse brain in a common three-dimensional (3D) space. The T2*, quantitative susceptibility mapping, diffusion tensor imaging, and neurite orientation dispersion and density imaging parameters were compared with both serial two-photon tomography images and 3D Nissl staining images in the CCFv3 at the same spatial resolution. The correlation between MRI and Nissl staining strongly depends on different metrics and different regions of the brain. Integrating different imaging modalities to the same space may substantially improve our understanding of the complexity of the brain at different scales.

Radiomic texture analysis based on neurite orientation dispersion and density imaging to differentiate glioblastoma from solitary brain metastasis.

BACKGROUND: We created discriminative models of different regions of interest (ROIs) using radiomic texture features of neurite orientation dispersion and density imaging (NODDI) and evaluated the feasibility of each model in differentiating glioblastoma multiforme (GBM) from solitary brain metastasis (SBM). METHODS: We conducted a retrospective study of 204 patients with GBM (n = 146) or SBM (n = 58). Radiomic texture features were extracted from five ROIs based on three metric maps (intracellular volume fraction, orientation dispersion index, and isotropic volume fraction of NODDI), including necrosis, solid tumors, peritumoral edema, tumor bulk volume (TBV), and abnormal bulk volume. Four feature selection methods and eight classifiers were used for the radiomic texture feature selection and model construction. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the models. Routine magnetic resonance imaging (MRI) radiomic texture feature models generated in the same manner were used for the horizontal comparison. RESULTS: NODDI-radiomic texture analysis based on TBV subregions exhibited the highest accuracy (although nonsignificant) in differentiating GBM from SBM, with area under the ROC curve (AUC) values of 0.918 and 0.882 in the training and test datasets, respectively, compared to necrosis (AUCtraining:0.845, AUCtest:0.714), solid tumor (AUCtraining:0.852, AUCtest:0.821), peritumoral edema (AUCtraining:0.817, AUCtest:0.762), and ABV (AUCtraining:0.834, AUCtest:0.779). The performance of the five ROI radiomic texture models in routine MRI was inferior to that of the NODDI-radiomic texture model. CONCLUSION: Preoperative NODDI-radiomic texture analysis based on TBV subregions shows great potential for distinguishing GBM from SBM.

Histogram Analysis Based on Neurite Orientation Dispersion and Density MR Imaging for Differentiation Between Glioblastoma Multiforme and Solitary Brain Metastasis and Comparison of the Diagnostic Performance of Two ROI Placements.

BACKGROUND: Preoperative differentiation of glioblastoma multiforme (GBM) and solitary brain metastasis (SBM) contributes to guide neurosurgical decision-making. PURPOSE: To explore the value of histogram analysis based on neurite orientation dispersion and density imaging (NODDI) in differentiating between GBM and SBM and comparison of the diagnostic performance of two region of interest (ROI) placements. STUDY TYPE: Retrospective. POPULATION: In all, 109 patients with GBM (n = 57) or SBM (n = 52) were enrolled. FIELD STRENGTH/SEQUENCE: A 3.0 T scanners. T2 -dark-fluid sequence, contrast-enhanced T1 magnetization-prepared rapid gradient echo sequence, and NODDI. ASSESSMENT: ROIs were placed on the peritumoral edema area (ROI1) and whole tumor area (ROI2, included the cystic, necrotic, and hemorrhagic areas). Histogram parameters of each isotropic volume fraction (ISOVF), intracellular volume fraction (ICVF), and orientation dispersion index (ODI) from NODDI images for two ROIs were calculated, respectively. STATISTICAL TESTS: Mann-Whitney U test, independent t-test, chi-square test, multivariate logistic regression analysis, DeLong's test. RESULTS: For the ROI1 and ROI2, the ICVFmin and ODImean obtained the highest area under curve (AUC, AUC = 0.741 and 0.750, respectively) compared to other single parameters, and the AUC of the multivariate logistic regression model was 0.851 and 0.942, respectively. DeLong's test revealed significant difference in diagnostic performance between optimal single parameter and multivariate logistic regression model within the same ROI, and the multivariate logistic regression models between two different ROIs. DATA CONCLUSION: The performance of multivariate logistic regression model is superior to optimal single parameter in both ROIs based on NODDI histogram analysis to distinguish SBM from GBM, and the ROI placed on the whole tumor area exhibited better diagnostic performance. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Astrogliosis, neuritic microstructure, and sex effects: GFAP is an indicator of neuritic orientation in women.

BACKGROUND: Data from human studies suggest that immune dysregulation is associated with Alzheimer's disease (AD) pathology and cognitive decline and that neurites may be affected early in the disease trajectory. Data from animal studies further indicate that dysfunction in astrocytes and inflammation may have a pivotal role in facilitating dendritic damage, which has been linked with negative cognitive outcomes. To elucidate these relationships further, we have examined the relationship between astrocyte and immune dysregulation, AD-related pathology, and neuritic microstructure in AD-vulnerable regions in late life. METHODS: We evaluated panels of immune, vascular, and AD-related protein markers in blood and conducted in vivo multi-shell neuroimaging using Neurite Orientation Dispersion and Density Imaging (NODDI) to assess indices of neuritic density (NDI) and dispersion (ODI) in brain regions vulnerable to AD in a cohort of older adults (n = 109). RESULTS: When examining all markers in tandem, higher plasma GFAP levels were strongly related to lower neurite dispersion (ODI) in grey matter. No biomarker associations were found with higher neuritic density. Associations between GFAP and neuritic microstructure were not significantly impacted by symptom status, APOE status, or plasma Aß42/40 ratio; however, there was a large sex effect observed for neurite dispersion, wherein negative associations between GFAP and ODI were only observed in females. DISCUSSION: This study provides a comprehensive, concurrent appraisal of immune, vascular, and AD-related biomarkers in the context of advanced grey matter neurite orientation and dispersion methodology. Sex may be an important modifier of the complex associations between astrogliosis, immune dysregulation, and brain microstructure in older adults.

Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging.

OBJECTIVES: To compare the histogram features of multiple diffusion metrics in predicting the grade and cellular proliferation of meningiomas. METHODS: Diffusion spectrum imaging was performed in 122 meningiomas (30 males, 13-84 years), which were divided into 31 high-grade meningiomas (HGMs, grades 2 and 3) and 91 low-grade meningiomas (LGMs, grade 1). The histogram features of multiple diffusion metrics obtained from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) in the solid tumours were analysed. All values between the two groups were compared with the Man-Whitney U test. Logistic regression analysis was applied to predict meningioma grade. The correlation between diffusion metrics and Ki-67 index was analysed. RESULTS: The DKI_AK (axial kurtosis) maximum, DKI_AK range, MAP_RTPP (return-to-plane probability) maximum, MAP_RTPP range, NODDI_ICVF (intracellular volume fraction) range, and NODDI_ICVF maximum values were lower (p < 0.0001), whilst the DTI_MD (mean diffusivity) minimum values were higher in LGMs than those in HGMs (p < 0.001). Amongst the DTI, DKI, MAP, NODDI, and combined diffusion models, no significant differences were found in areas under the receiver operating characteristic curves (AUCs) for grading meningiomas (AUCs, 0.75, 0.75, 0.80, 0.79, and 0.86, respectively; all corrected p > 0.05, Bonferroni correction). Significant but weak positive correlations were found between the Ki-67 index and DKI, MAP, and NODDI metrics (r = 0.26-0.34, all p < 0.05). CONCLUSIONS: Whole tumour histogram analyses of the multiple diffusion metrics from four diffusion models are promising methods in grading meningiomas. The DTI model has similar diagnostic performance compared with advanced diffusion models. KEY POINTS: • Whole tumour histogram analyses of multiple diffusion models are feasible for grading meningiomas. • The DKI, MAP, and NODDI metrics are weakly associated with the Ki-67 proliferation status. • DTI has similar diagnostic performance compared with DKI, MAP, and NODDI in grading meningiomas.

Demonstration of brain region-specific neuronal vulnerability in human iPSC-based model of familial Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by protein inclusions mostly composed of aggregated forms of α-synuclein (α-Syn) and by the progressive degeneration of midbrain dopaminergic neurons (mDANs), resulting in motor symptoms. While other brain regions also undergo pathologic changes in PD, the relevance of α-Syn aggregation for the preferential loss of mDANs in PD pathology is not completely understood yet. To elucidate the mechanisms of the brain region-specific neuronal vulnerability in PD, we modeled human PD using human-induced pluripotent stem cells (iPSCs) from familial PD cases with a duplication (Dupl) of the α-Syn gene (SNCA) locus. Human iPSCs from PD Dupl patients and a control individual were differentiated into mDANs and cortical projection neurons (CPNs). SNCA dosage increase did not influence the differentiation efficiency of mDANs and CPNs. However, elevated α-Syn pathology, as revealed by enhanced α-Syn insolubility and phosphorylation, was determined in PD-derived mDANs compared with PD CPNs. PD-derived mDANs exhibited higher levels of reactive oxygen species and protein nitration levels compared with CPNs, which might underlie elevated α-Syn pathology observed in mDANs. Finally, increased neuronal death was observed in PD-derived mDANs compared to PD CPNs and to control mDANs and CPNs. Our results reveal, for the first time, a higher α-Syn pathology, oxidative stress level, and neuronal death rate in human PD mDANs compared with PD CPNs from the same patient. The finding implies the contribution of pathogenic α-Syn, probably induced by oxidative stress, to selective vulnerability of substantia nigra dopaminergic neurons in human PD.

Synaptic activity-induced glycolysis facilitates membrane lipid provision and neurite outgrowth.

The formation of neurites is an important process affecting the cognitive abilities of an organism. Neurite growth requires the addition of new membranes, but the metabolic remodeling necessary to supply lipids for membrane expansion is poorly understood. Here, we show that synaptic activity, one of the most important inducers of neurite growth, transcriptionally regulates the expression of neuronal glucose transporter Glut3 and rate-limiting enzymes of glycolysis, resulting in enhanced glucose uptake and metabolism that is partly used for lipid synthesis. Mechanistically, CREB regulates the expression of Glut3 and Siah2, the latter and LDH activity promoting the normoxic stabilization of HIF-1α that regulates the expression of rate-limiting genes of glycolysis. The expression of dominant-negative HIF-1α or Glut3 knockdown blocks activity-dependent neurite growth in vitro while pharmacological inhibition of the glycolysis and specific ablation of HIF-1α in early postnatal mice impairs the neurite architecture. These results suggest that the manipulation of neuronal glucose metabolism could be used to treat some brain developmental disorders.

Vascular Endothelial Growth Factor Mediates the Sprouted Axonogenesis of Breast Cancer in Rat.

Nerve infiltration into the tumor is a common feature of the tumor microenvironment. The mechanisms of axonogenesis in breast cancer remain unclear. We hypothesized that vascular endothelial growth factor (VEGF), as well as nerve growth factor (NGF), is involved in the axonogenesis of breast cancer. A N-methyl-N-nitrosourea (MNU)-induced rat model of breast cancer was used to explore the presence of axonogenesis in breast tumor and the involvement of VEGF, as well as NGF, in the axonogenesis of breast tumor. Nerve infiltration into the tumor was found in MNU-induced rat model of breast cancer including the sensory and sympathetic nerve fibers. Nerve density was increased following the growth of tumor. The sensory neurons innervating the thoracic and abdominal mammary tumors peaked at T5 to T6 and L1 to L2 dorsal root ganglions, respectively. Either VEGF receptor inhibitor or antibody against VEGF receptor 2, as well as NGF receptor inhibitor, apparently decreased both the nerve density and vascular density of breast tumor. The reduced nerve density was correlated with the decreased vascular density induced by these treatments. In cultured dorsal root ganglion neurons, phosphatidylinositol 3 (PI3K)/Akt, extracellular signal-regulated protein kinase (ERK), and p38 inhibitors significantly attenuated VEGF-induced neurite elongation. These findings provide direct evidence that VEGF, as well as NGF, may control the axonogenesis of breast cancer.

Decreased FAK activity and focal adhesion dynamics impair proper neurite formation of medium spiny neurons in Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder caused by a polyglutamine expansion in the protein huntingtin (HTT) [55]. While the final pathological consequence of HD is the neuronal cell death in the striatum region of the brain, it is still unclear how mutant HTT (mHTT) causes synaptic dysfunctions at the early stage and during the progression of HD. Here, we discovered that the basal activity of focal adhesion kinase (FAK) is severely reduced in a striatal HD cell line, a mouse model of HD, and the human post-mortem brains of HD patients. In addition, we observed with a FRET-based FAK biosensor [59] that neurotransmitter-induced FAK activation is decreased in HD striatal neurons. Total internal reflection fluorescence (TIRF) imaging revealed that the reduced FAK activity causes the impairment of focal adhesion (FA) dynamics, which further leads to the defect in filopodial dynamics causing the abnormally increased number of immature neurites in HD striatal neurons. Therefore, our results suggest that the decreased FAK and FA dynamics in HD impair the proper formation of neurites, which is crucial for normal synaptic functions [52]. We further investigated the molecular mechanism of FAK inhibition in HD and surprisingly discovered that mHTT strongly associates with phosphatidylinositol 4,5-biphosphate, altering its normal distribution at the plasma membrane, which is crucial for FAK activation [14, 60]. Therefore, our results provide a novel molecular mechanism of FAK inhibition in HD along with its pathological mechanism for synaptic dysfunctions during the progression of HD.

In vivo detection of damage in multiple sclerosis cortex and cortical lesions using NODDI.

OBJECTIVE: To characterise in vivo the microstructural abnormalities of multiple sclerosis (MS) normal-appearing (NA) cortex and cortical lesions (CLs) and their relations with clinical phenotypes and disability using neurite orientation dispersion and density imaging (NODDI). METHODS: One hundred and seventy-two patients with MS (101 relapsing-remitting multiple sclerosis (RRMS), 71 progressive multiple sclerosis (PMS)) and 62 healthy controls (HCs) underwent a brain 3T MRI. Brain cortex and CLs were segmented from three-dimensional T1-weighted and double inversion recovery sequences. Using NODDI on diffusion-weighted sequence, intracellular volume fraction (ICV_f) and Orientation Dispersion Index (ODI) were assessed in NA cortex and CLs with default or optimised parallel diffusivity for the cortex (D//=1.7 or 1.2 µm2/ms, respectively). RESULTS: The NA cortex of patients with MS had significantly lower ICV_f versus HCs' cortex with both D// values (false discovery rate (FDR)-p <0.001). CLs showed significantly decreased ICV_f and ODI versus NA cortex of both HCs and patients with MS with both D// values (FDR-p ≤0.008). Patients with PMS versus RRMS had significantly decreased NA cortex ICV_f and ODI (FDR-p=0.050 and FDR-p=0.032) with only D//=1.7 µm2/ms. No CL microstructural differences were found between MS clinical phenotypes. MS NA cortex ICV_f and ODI were significantly correlated with disease duration, clinical disability, lesion burden and global and regional brain atrophy (r from -0.51 to 0.71, FDR-p from <0.001 to 0.045). CONCLUSIONS: A significant neurite loss occurs in MS NA cortex. CLs show a further neurite density reduction and a reduced ODI suggesting a simplification of neurite complexity. NODDI is relevant to investigate in vivo the heterogeneous pathology affecting the MS cortex.