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.

Association of adverse childhood experiences and cortical neurite density alterations with posttraumatic stress disorder symptoms in autism spectrum disorder

Background

Posttraumatic stress disorder (PTSD) can be a source of significant social and daily distress in autism spectrum disorder (ASD). Compared to typically developed (TD) individuals, people with ASD are at an increased risk of adverse childhood experiences (ACEs), which can result in abnormal neuronal development. However, whether or how ACEs influence abnormal neural development and PTSD symptoms in ASD has not been fully elucidated.

Methods

Thirty-nine TD individuals and 41 individuals with ASD underwent T1-weighted magnetic resonance imaging and neurite orientation dispersion and density imaging (NODDI), with axonal and dendritic densities assessed in terms of the orientation dispersion index and neurite density index (NDI), respectively. Voxel-based analyses were performed to explore the brain regions associated with PTSD symptoms, and the relationships between the severity of ACEs and PTSD symptoms and NODDI parameters in the extracted brain regions were examined.

Results

There was a significant positive association between PTSD symptom severity and NDI in the bilateral supplementary motor area; right superior frontal, left supramarginal, and right superior temporal gyrus; and right precuneus in the ASD group, but not in the TD group. ACE severity was significantly associated with NDI in the right superior frontal and left supramarginal gyrus and right precuneus in the ASD group. Moreover, NDI in the right precuneus mainly predicted the severity of PTSD symptoms in the ASD group, but not the TD group.

Conclusion

These results suggest that ACE-associated higher neurite density is of clinical importance in the pathophysiology of PTSD symptoms in ASD.

Structural and diffusion-weighted brain imaging predictors of attention-deficit/hyperactivity disorder and its symptomology in very young (4- to 7-year-old) children

The current study aimed to identify the key neurobiology of attention-deficit/hyperactivity disorder (ADHD), as it relates to ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. To do so, we adapted a predictive modelling approach to identify the key structural and diffusion-weighted brain imaging measures and their relative standing with respect to teacher ratings of executive function (EF) (measured by the Metacognition Index of the Behavior Rating Inventory of Executive Function [BRIEF]) and negativity and emotion regulation (ER) (measured by the Emotion Regulation Checklist [ERC]), in a critical young age range (ages 4 to 7, mean age 5.52 years, 82.2% Hispanic/Latino), where initial contact with educators and clinicians typically take place. Teacher ratings of EF and ER were predictive of both ADHD diagnostic category and symptoms of hyperactive/impulsive behaviour and inattention. Among the neural measures evaluated, the current study identified the critical importance of the largely understudied diffusion-weighted imaging measures for the underlying neurobiology of ADHD and its associated symptomology. Specifically, our analyses implicated the inferior frontal gyrus as a critical predictor of ADHD diagnostic category and its associated symptomology, above and beyond teacher ratings of EF and ER. Collectively, the current set of findings have implications for theories of ADHD, the relative utility of neurobiological measures with respect to teacher ratings of EF and ER, and the developmental trajectory of its underlying neurobiology.

Gradual changes in microarchitectural properties of cortex and juxtacortical white matter: Observed by anatomical and diffusion MRI

PURPOSE

Characterization of cerebral cortex is challenged by the complexity and heterogeneity of its cyto- and myeloarchitecture. This study evaluates quantitative MRI metrics, measured across two cortical depths and in subcortical white matter (WM) adjacent to cortex (juxtacortical WM), indicative of myelin content, neurite density, and diffusion microenvironment, for a comprehensive characterization of cortical microarchitecture.

METHODS

High-quality structural and diffusion MRI data (N = 30) from the Human Connectome Project were processed to compute myelin index, neurite density index, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity from superficial cortex, deep cortex, and juxtacortical WM. The distributional patterns of these metrics were analyzed individually, correlated to one another, and were compared to established parcellations.

RESULTS

Our results supported that myeloarchitectonic and the coexisting cytoarchitectonic structures influence the diffusion properties of water molecules residing in cortex. Full cortical thickness showed myelination patterns similar to those previously observed in humans. Higher myelin indices with similar distributional patterns were observed in deep cortex whereas lower myelin indices were observed in superficial cortex. Neurite density index and other diffusion MRI derived parameters provided complementary information to myelination. Reliable and reproducible correlations were identified among the cortical microarchitectural properties and fiber distributional patterns in proximal WM structures.

CONCLUSION

We demonstrated gradual changes across the cortical sheath by assessing depth-specific cortical micro-architecture using anatomical and diffusion MRI. Mutually independent but coexisting features of cortical layers and juxtacortical WM provided new insights towards structural organizational units and variabilities across cortical regions and through depth.

Frontal grey matter microstructure is associated with sleep slow waves characteristics in late midlife

STUDY OBJECTIVES

The ability to generate slow waves (SW) during non-rapid eye movement (NREM) sleep decreases as early as the 5th decade of life, predominantly over frontal regions. This decrease may concern prominently SW characterized by a fast switch from hyperpolarized to depolarized, or down-to-up, state. Yet, the relationship between these fast and slow switcher SW and cerebral microstructure in ageing is not established.

METHODS

We recorded habitual sleep under EEG in 99 healthy late midlife individuals (mean age = 59.3 ± 5.3 years; 68 women) and extracted SW parameters (density, amplitude, frequency) for all SW as well as according to their switcher type (slow vs. fast). We further used neurite orientation dispersion and density imaging (NODDI) to assess microstructural integrity over a frontal grey matter region of interest (ROI).

RESULTS

In statistical models adjusted for age, sex, and sleep duration, we found that a lower SW density, particularly for fast switcher SW, was associated with a reduced orientation dispersion of neurites in the frontal ROI (p = 0.018, R2β* = 0.06). In addition, overall SW frequency was positively associated with neurite density (p = 0.03, R2β* = 0.05). By contrast, we found no significant relationships between SW amplitude and NODDI metrics.

CONCLUSIONS

Our findings suggest that the complexity of neurite organization contributes specifically to the rate of fast switcher SW occurrence in healthy middle-aged individuals, corroborating slow and fast switcher SW as distinct types of SW. They further suggest that the density of frontal neurites plays a key role for neural synchronization during sleep.

TRIAL REGISTRATION NUMBER

EudraCT 2016-001436-35.

Subjective cognitive decline predicts lower cingulo-opercular network functional connectivity in individuals with lower neurite density in the forceps minor: Cingulo-opercular network in SCD

Cognitive complaints of attention/concentration problems are highly frequent in older adults with subjective cognitive decline (SCD). Functional connectivity in the cingulo-opercular network (CON-FC) supports cognitive control, tonic alertness, and visual processing speed. Thus, those complaints in SCD may reflect a decrease in CON-FC. Frontal white-matter tracts such as the forceps minor exhibit age- and SCD-related alterations and, therefore, might influence the CON-FC decrease in SCD. Here, we aimed to determine whether SCD predicts an impairment in CON-FC and whether neurite density in the forceps minor modulates that effect. To do so, we integrated cross-sectional and longitudinal analyses of multimodal data in a latent growth curve modeling approach. Sixty-nine healthy older adults (13 males; 68.33 ± 7.95 years old) underwent resting-state functional and diffusion-weighted magnetic resonance imaging, and the degree of SCD was assessed at baseline with the memory functioning questionnaire (greater score indicating more SCD). Forty-nine of the participants were further enrolled in two follow-ups, each about 18 months apart. Baseline SCD did not predict CON-FC after three years or its rate of change (p-values > 0.092). Notably, however, the forceps minor neurite density did modulate the relation between SCD and CON-FC (intercept; b = 0.21, 95% confidence interval, CI, [0.03, 0.39], p = 0.021), so that SCD predicted a greater CON-FC decrease in older adults with relatively lower neurite density in the forceps minor. The neurite density of the forceps minor, in turn, negatively correlated with age. These results suggest that CON-FC alterations in SCD are dependent upon the forceps minor neurite density. Accordingly, these results imply modifiable age-related factors that could help delay or mitigate both age and SCD-related effects on brain connectivity.

Single-shell NODDI using dictionary-learner-estimated isotropic volume fraction

Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular, and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize brain tissue microstructure. Single-shell reconstruction for NODDI parameters has been discouraged in previous studies caused by failure when fitting, especially for the neurite density index (NDI). Here, we investigated the possibility of creating robust NODDI parameter maps with single-shell data, using the isotropic volume fraction (f_ISO ) as a prior. Prior estimation was made independent of the NODDI model constraint using a dictionary learning approach. First, we used a stochastic sparse dictionary-based network (DictNet), which is trained with data obtained from in vivo and simulated diffusion MRI data, to predict f_ISO . In single-shell cases, the mean diffusivity and raw T₂ signal with no diffusion weighting (S₀ ) was incorporated in the dictionary for the f_ISO estimation. Then, the NODDI framework was used with the known f_ISO to estimate the NDI and orientation dispersion index (ODI). The f_ISO estimated using our model was compared with other f_ISO estimators in the simulation. Further, using both synthetic data simulation and human data collected on a 3 T scanner (both high-quality HCP and clinical dataset), we compared the performance of our dictionary-based learning prior NODDI (DLpN) with the original NODDI for both single-shell and multi-shell data. Our results suggest that DLpN-derived NDI and ODI parameters for single-shell protocols are comparable with original multi-shell NODDI, and the protocol with b = 2000 s/mm² performs the best (error ~ 5% in white and gray matter). This may allow NODDI evaluation of studies on single-shell data by multi-shell scanning of two subjects for DictNet f_ISO training.

Neurite density imaging in amygdala nuclei reveals interindividual differences in neuroticism

Neuroticism is known to have significant health implications. While previous research revealed that interindividual differences in the amygdala function are associated with interindividual differences in neuroticism, the impact of the amygdala’s structure and especially microstructure on variations in neuroticism remains unclear. Here, we present the first study using NODDI to examine the association between the in vivo microstructural architecture of the amygdala and neuroticism at the level of neurites. We, therefore, acquired brain images from 221 healthy participants using advanced multi‐shell diffusion‐weighted imaging. Because the amygdala comprises several nuclei, we, moreover, used a high‐resolution T1 image to automatically segment the amygdala into eight different nuclei. Neuroticism and its facets have been assessed using the NEO‐PI‐R. Finally, we associated neuroticism and its facets with the volume and microstructure of the amygdala nuclei. Statistical analysis revealed that lower neurite density in the lateral amygdala nucleus (La) was significantly associated with higher scores in depression, one of the six neuroticism facets. The La is the sensory relay of the amygdala, filtering incoming information based on previous experiences. Reduced neurite density and related changes in the dendritic structure of the La could impair its filtering function. This again might cause harmless sensory information to be misevaluated as threatening and lead to the altered amygdala responsivity as reported in previous studies investigating the functional correlates of neuroticism and neuroticism‐related disorders like depression.

Brain Development From Newborn to Adolescence: Evaluation by Neurite Orientation Dispersion and Density Imaging

Neurite orientation dispersion and density imaging (NODDI) is a diffusion model specifically designed for brain magnetic resonance imaging. Despite recent studies suggesting that NODDI modeling might be more sensitive to brain development than diffusion tensor imaging (DTI), these studies were limited to a relatively small age range and mainly based on the manually operated region of interest analysis. Therefore, this study applied NODDI to investigate brain development in a large sample size of 214 subjects ranging in ages from 0 to 14. The whole brain was automatically segmented into 122 regions. The maturation trajectory of each region was characterized by the time course of diffusion metrics and further quantified using nonlinear regression. The NODDI-derived metrics, neurite density index (NDI) and orientation dispersion index (ODI), increased with age. And these two metrics were superior to the DTI-derived metrics in SVM regression models of age. The NDI in white matter exhibited a more rapid growth than that in gray matter (including the cortex and deep nucleus). These diffusion indicators experienced conspicuous increases during early childhood and the growth speed slowed down in adolescence. Region-specific maturation patterns were described throughout the brain, including white matter, cortical and deep gray matter. These development patterns were evaluated and discussed on the basis of NODDI’s model assumptions. To summarize, this study verified the high sensitivity of NODDI to age over a crucial developmental period from newborn to adolescence. Moreover, the existing knowledge of brain development has been complemented, suggesting that NODDI has a potential capability in the investigation of brain development.

Neurite Orientation Dispersion and Density Imaging (NODDI) and Duration of Untreated Psychosis in Antipsychotic Medication-Naïve First Episode Psychosis Patients

Background

Diffusion tensor imaging suggests that white matter alterations are already evident in first episode psychosis patients (FEP) and may become more prominent as the duration of untreated psychosis (DUP) increases. But because the tensor model lacks specificity, it remains unclear how to interpret findings on a biological level. Here, we used a biophysical diffusion model, Neurite Orientation Dispersion and Density Imaging (NODDI), to map microarchitecture in FEP, and to investigate associations between DUP and microarchitectural integrity.

Methods

We scanned 78 antipsychotic medication-naïve FEP and 64 healthy controls using a multi-shell diffusion weighted sequence and used the NODDI toolbox to compute neurite density (ND), orientation dispersion index (ODI) and extracellular free water (FW) maps. AFNI's 3dttest++ was used to compare diffusion maps between groups and to perform regression analyses with DUP.

Results

We found that ND was decreased in commissural and association fibers but increased in projection fibers in FEP. ODI was largely increased regardless of fiber type, and FW showed a mix of increase in decrease across fiber tracts. We also demonstrated associations between DUP and microarchitecture for all NODDI indices.

Conclusions

We demonstrated that complex microarchitecture abnormalities are already evident in antipsychotic-naïve FEP. ND alterations are differentially expressed depending on fiber type, while decreased fiber complexity appears to be a uniform marker of white matter deficit in the illness. Importantly, we identified an empirical link between longer DUP and greater white matter pathology across NODDI indices, underscoring the critical importance of early intervention in this devastating illness.

Traumatic brain injury: a comparison of diffusion and volumetric magnetic resonance imaging measures

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate-severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed.

Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism

Neurite orientation dispersion and density imaging (NODDI) uses a three-compartment model to probe brain tissue microstructure, whereas free-water (FW) imaging models two-compartments. It is unknown if NODDI detects more disease-specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi- and single-shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi-shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single-shell; FW; free-water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.

Application of neurite orientation dispersion and density imaging to characterize brain microstructural abnormalities in type-2 diabetics with mild cognitive impairment

BACKGROUND

Diffusion-tensor-imaging (DTI) is sensitive in detecting white matter changes in type-2 diabetes mellitus (T2DM). However, DTI indices can be affected by either neurite density or spatial variation. A novel diffusion MRI technique, termed neurite orientation dispersion and density imaging (NODDI), can provide distinct indices of fiber density and dispersion.

PURPOSE

To characterize brain microstructural alterations in T2DM patients with mild cognitive impairment (MCI) using the NODDI model.

STUDY TYPE

Cross-sectional.

SUBJECTS

Twenty T2DM patients with (DM-MCI group), 18 age- and gender-matched T2DM patients with normal cognition (DM-NC group), and 28 euglycemic healthy controls (HC).

FIELD STRENGTH/SEQUENCE

3T/NODDI.

ASSESSMENT

Diffusion data were analyzed using tract-based-spatial-statistics (TBSS) analysis in white matter and voxel-based analysis in both white and gray matter. NODDI indices, including intracellular volume fraction (Vic) and orientation dispersion index (ODI), were estimated from multiple regions and compared among these groups.

STATISTICAL TESTS

Differences between groups were compared by Student's t-test, Pearson chi-square test, or analysis of variance when appropriate. Correlation analyses were performed to investigate the relationship between NODDI variables and clinical measurements.

RESULTS

Whole-brain TBSS revealed that 2.29% and 2.02% of the white matter regions exhibited decreased fractional anisotropy and Vic, respectively, between the DM-NC and HC, while considerably larger white matter areas showed decreased fractional anisotropy (38.38%) and Vic (34.64%) between the DM-MCI and HC (Student's t-test, P < 0.05). However, the angular variation of neurites, characterized by ODI, exhibited very little (0.1%, P < 0.05) or no difference (P > 0.05) between either the DM-MCI or DM-NC groups and HC. Decreased Vic values in the genu of the corpus callosum (R = 0.580, 0.551 and 0.586, P < 0.01) and thalamus (R = 0.570, 0.616, and 0.595, P < 0.05) correlated with glycosylated hemoglobin A1c level, disease duration, and neuropsychological scores, respectively.

DATA CONCLUSION

T2DM patients with cognitive decline had reduced Vic, which indicated decreased density of axons and dendrites. NODDI might be able to help probe microstructural changes in white and gray matter and provide information on diabetic encephalopathy, including those with cognitive impairment.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:889-898.

Restriction spectrum imaging of white matter and its relation to neurological disability in multiple sclerosis

BACKGROUND

Restriction spectrum imaging (RSI) is a recently introduced magnetic resonance imaging diffusion technique. The utility of RSI in multiple sclerosis (MS) is unknown.

OBJECTIVE

To investigate the association between RSI-derived parameters and neurological disability in MS.

METHODS

Seventy-seven relapsing-remitting MS patients were scanned with RSI on a 3-T scanner. RSI-derived parameters: fast and slow apparent diffusion coefficient (sADC), fractional anisotropy, restricted fractional anisotropy, neurite density (ND), cellularity, extracellular water fraction, and free water fraction, were obtained in white matter lesions (WML) and normal appearing white matter (NAWM). Patients were divided into three groups according to their expanded disability status scale (EDSS): with minimal, low, and substantial disability (<2.5, 2.5-3, and >3, respectively). Group comparisons and correlation analyses were performed.

RESULTS

All tested RSI-derived parameters differed between WML and NAWM ( p < 0.001 for all pairwise comparisons). The sADC in WML showed largest difference across disability subgroups (analysis of variance (ANOVA): F = 5.1, η² = 0.12, p = 0.008). ND in NAWM showed strongest correlation with disability (ϱ = -0.39, p < 0.001).

CONCLUSION

The strongest correlation with EDSS of ND obtained in NAWM indicates that processes outside lesions are important for disability in MS. Our study suggests that RSI-derived parameters may help understand the "clinico-radiological paradox" and improve disease monitoring in MS.

NODDI reproducibility and variability with magnetic field strength: A comparison between 1.5 T and 3 T

Diffusion models are advantageous for examining brain microstructure non-invasively and their validation is important for transference into the clinical domain. Neurite Orientation Dispersion and Density Imaging (NODDI) is a promising model for estimating multiple diffusion compartments from MRI data acquired in a clinically feasible time. As a relatively new model, it is necessary to examine NODDI under certain experimental conditions, such as change in magnetic field-strength, and assess it in relation to diffusion tensor imaging (DTI), an established model that is largely understood by the neuroimaging community. NODDI measures (intracellular volume fraction, ν_ic , and orientation distribution, OD) were compared with DTI at 1.5 and 3 T data in healthy adults in whole-brain tissue masks and regions of white- and deep grey-matter. Within-session reproducibility and between-subject differences of NODDI with field-strength were also investigated. Field-strength had a significant effect on NODDI measures, suggesting careful interpretation of results from data acquired at 1.5 and 3 T. It was demonstrated that NODDI is feasible at 1.5 T, but with lower ν_ic in white-matter regions compared with 3 T. Furthermore, the advantages of NODDI over DTI in a region of complex microstructure were shown. Specifically, in the centrum-semiovale where FA is typically as low as in grey-matter, ν_ic was comparable to other white-matter regions yet accompanied by an OD similar to deep grey-matter. In terms of reproducibility, NODDI measures varied more than DTI. It may be that NODDI is more susceptible to noisier parameter estimates when compared with DTI, conversely it may have greater sensitivity to true within- and between-subject heterogeneity. Hum Brain Mapp 37:4550-4565, 2016. © 2016 Wiley Periodicals, Inc.

Reduced Neurite Density in Neuronal Cell Cultures Exposed to Serum of Patients with Bipolar Disorder

BACKGROUND

Increased inflammatory markers and oxidative stress have been reported in serum among patients with bipolar disorder (BD). The aim of this study is to assess whether biochemical changes in the serum of patients induces neurotoxicity in neuronal cell cultures.

METHODS

We challenged the retinoic acid-differentiated human neuroblastoma SH-SY5Y cells with the serum of BD patients at early and late stages of illness and assessed neurite density and cell viability as neurotoxic endpoints.

RESULTS

Decreased neurite density was found in neurons treated with the serum of patients, mostly patients at late stages of illness. Also, neurons challenged with the serum of late-stage patients showed a significant decrease in cell viability.

CONCLUSIONS

Our findings showed that the serum of patients with bipolar disorder induced a decrease in neurite density and cell viability in neuronal cultures.

Degradation of the electrospun silica nanofiber in a biological medium for primary hippocampal neuron - effect of surface modification

In this work, silica nanofibers (SNFs) were prepared by an electrospinning method and modified with poly-d-lysine (PDL) or (3-aminopropyl) trimethoxysilane (APTS) making biocompatible and degradable substrates for neuronal growth. The as-prepared SNF, modified SNF-PDL, and SNF-APTS were evaluated using scanning electron microscopy, nitrogen adsorption/desorption isotherms, contact angle measurements, and inductively coupled plasma atomic emission spectroscopy. Herein, the scanning electron microscopic images revealed that dissolution occurred in a corrosion-like manner by enlarging porous structures, which led to loss of structural integrity. In addition, covalently modified SNF-APTS with more hydrophobic surfaces and smaller surface areas resulted in significantly slower dissolution compared to SNF and physically modified SNF-PDL, revealing that different surface modifications can be used to tune the dissolution rate. Growth of primary hippocampal neuron on all substrates led to a slower dissolution rate. The three-dimensional SNF with larger surface area and higher surface density of the amino group promoted better cell attachment and resulted in an increased neurite density. This is the first known work addressing the degradability of SNF substrate in physiological conditions with neuron growth in vitro, suggesting a strong potential for the applications of the material in controlled drug release.