No abstract

Within cancer, there is a large wealth of diversity, complexity, and information that nature has engineered rendering it challenging to identify reliable detection methods. Therefore, the development of simple and effective techniques to delineate the fine characteristics of cancer cells can have great potential impacts on cancer diagnosis and treatment. Herein, we report a magnetic glyco-nanoparticle (MGNP) based nanosensor system bearing carbohydrates as the ligands, not only to detect and differentiate cancer cells but also to quantitatively profile their carbohydrate binding abilities by magnetic resonance imaging (MRI). Using an array of MGNPs, a range of cells including closely related isogenic tumor cells, cells with different metastatic potential and malignant vs normal cells can be readily distinguished based on their respective "MRI signatures". Furthermore, the information obtained from such studies helped guide the establishment of strongly binding MGNPs as antiadhesive agents against tumors. As the interactions between glyco-conjugates and endogenous lectins present on cancer cell surface are crucial for cancer development and metastasis, the ability to characterize and unlock the glyco-code of individual cell lines can facilitate both the understanding of the roles of carbohydrates as well as the expansion of diagnostic and therapeutic tools for cancer.

Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3-9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter.

Purpose:To compare the diagnostic performances of three T1-weighted 3.0-T magnetic resonance (MR) sequences at carotid intraplaque hemorrhage (IPH) imaging, with histologic analysis as the reference standard. Materials and Methods:Institutional review board approval and informed consent were obtained for this HIPAA-compliant study. Twenty patients scheduled for carotid endarterectomy underwent 3.0-T carotid MR imaging, including two-dimensional fast spin-echo, three-dimensional time-of-fl ight (TOF), and three-dimensional magnetization-prepared rapid acquisition gradient-echo (RAGE) sequences. Two reviewers blinded to the histologic fi ndings assessed the presence, area, and signal intensity of IPH with each sequence. Detection statistics (sensitivity, specifi city, and Cohen k values) and agreement between area measurements (Pearson correlation coeffi cient [r] values) were calculated for each sequence. Results:When all 231 available MR sections were included for analysis, the magnetization-prepared RAGE ( k = 0.53) and fast spin-echo ( k = 0.42) sequences yielded moderate agreement between MR and histologic measurements, while the TOF sequence yielded fair agreement (k = 0.33). However, when 47 sections with either small IPHs or heavily calcifi ed IPHs were excluded, sensitivity, specifi city, and k values, respectively, were 80%, 97%, and 0.80 for magnetizationprepared RAGE imaging; 70%, 92%, and 0.63 for fast spinecho imaging; and 56%, 96%, and 0.57 for TOF imaging. MR imaging-histologic analysis correlation for IPH area was highest with magnetization-prepared RAGE imaging ( r = 0.813), followed by TOF ( r = 0.745) and fast spin-echo ( r = 0.497) imaging. The capability of these three sequences for IPH detection appeared to be in good agreement with the quantitative contrast of IPH versus background plaque tissue. Conclusion:The magnetization-prepared RAGE sequence, as compared with the fast spin-echo and TOF sequences, demonstrated higher diagnostic capability for the detection and quantifi cation of IPH. Potential limitations of 3.0-T IPH MR imaging are related to hemorrhage size and coexisting calcifi cation.q RSNA, 2010

Lewy body (LB) inclusions are one of the pathological hallmarks of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). One way to better understand the process leading to LB formation and associated pathogenesis responsible for neurodegeneration in PD and DLB is to examine the content of LB inclusions. Here, we performed a proteomic investigation of cortical LBs, obtained by laser capture microdissection from neurons in the temporal cortex of dementia patients with cortical LB disease. Analysis of over 2500 cortical LBs discovered 296 proteins; of those, 17 had been associated previously with brainstem and/or cortical LBs. We validated several proteins with immunohistochemical staining followed by confocal microscopy. The results demonstrated that heat shock cognate 71 kDa protein (also known as HSC70, HSP73, or HSPA10) was indeed not only colocalized with the majority of LBs in the temporal cortex but also colocalized to LBs in the frontal cortex of patients with diffuse LB disease. Our investigation represents the first extensive proteomic investigation of cortical LBs, and it is expected that characterization of the proteins in the cortical LBs may reveal novel mechanisms by which LB forms and pathways leading to neurodegeneration in DLB and/or advanced PD. Further investigation of these novel candidates is also necessary to ensure that the potential proteins in cortical LBs are not identified incorrectly because of incomplete current human protein database.

The cumulative effect of repetitive subconcussive collisions on the structural and functional integrity of the brain remains largely unknown. Athletes in collision sports, like football, experience a large number of impacts across a single season of play. The majority of these impacts, however, are generally overlooked, and their long-term consequences remain poorly understood. This study sought to examine the effects of repetitive collisions across a single competitive season in NCAA Football Bowl Subdivision athletes using advanced neuroimaging approaches. Players were evaluated before and after the season using multiple MRI sequences, including T1-weighted imaging, diffusion tensor imaging (DTI), arterial spin labeling (ASL), resting-state functional MRI (rs-fMRI), and susceptibility weighted imaging (SWI). While no significant differences were found between pre- and post-season for DTI metrics or cortical volumes, seed-based analysis of rs-fMRI revealed significant (p < 0.05) changes in functional connections to right isthmus of the cingulate cortex (ICC), left ICC, and left hippocampus. ASL data revealed significant (p < 0.05) increases in global cerebral blood flow (CBF), with a specific regional increase in right postcentral gyrus. SWI data revealed that 44% of the players exhibited outlier rates (p < 0.05) of regional decreases in SWI signal. Of key interest, athletes in whom changes in rs-fMRI, CBF and SWI were observed were more likely to have experienced high G impacts on a daily basis. These findings are indicative of potential pathophysiological changes in brain integrity arising from only a single season of participation in the NCAA Football Bowl Subdivision, even in the absence of clinical symptoms or a diagnosis of concussion. Whether these changes reflect compensatory adaptation to cumulative head impacts or more lasting alteration of brain integrity remains to be further explored.

The molecular mechanisms leading to neurodegeneration in Parkinson disease (PD) remain elusive, although many lines of evidence have indicated that ␣-synuclein and DJ-1, two critical proteins in PD pathogenesis, interact with each other functionally. The investigation on whether ␣-synuclein directly interacts with DJ-1 has been controversial. In the current study, we analyzed proteins associated with ␣-synuclein and/or DJ-1 with a robust proteomics technique called stable isotope labeling by amino acids in cell culture (SILAC) in dopaminergic MES cells exposed to rotenone versus controls. We identified 324 and 306 proteins in the ␣-synuclein-and DJ-1-associated protein complexes, respectively. Among ␣-synuclein-associated proteins, 141 proteins displayed significant changes in the relative abundance (increase or decrease) after rotenone treatment; among DJ-1-associated proteins, 119 proteins displayed significant changes in the relative abundance after rotenone treatment. Although no direct interaction was observed between ␣-synuclein and DJ-1, whether analyzed by affinity purification followed by mass spectrometry or subsequent direct co-immunoprecipitation, 144 proteins were seen in association with both ␣-synuclein and DJ-1. Of those, 114 proteins displayed significant changes in the relative abundance in the complexes associated with ␣-synuclein, DJ-1, or both after rotenone treatment. A subset of these proteins (mortalin, nucleolin, grp94, calnexin, and clathrin) was further validated for their association with both ␣-synuclein and DJ-1 using confocal microscopy, Western blot, and/or immunoprecipitation. Thus, we not only confirmed that there was no direct interaction between ␣-synuclein and DJ-1 but also, for the first time, report these five novel proteins to be associating with both ␣-synuclein and DJ-1. Further characterization of these docking proteins will likely shed more light on the mechanisms by which DJ-1 modulates the function of ␣-synuclein, and vice versa, in the setting of PD.

Advances in magnetic resonance (MR) imaging techniques enable the accurate measurements of cerebrospinal fluid (CSF) flow in the human brain. In addition, image reconstruction tools facilitate the collection of patient-specific brain geometry data such as the exact dimensions of the ventricular and subarachnoidal spaces (SAS) as well as the computer-aided reconstruction of the CSF-filled spaces. The solution of the conservation of CSF mass and momentum balances over a finite computational mesh obtained from the MR images predict the patients' CSF flow and pressure field. Advanced image reconstruction tools used in conjunction with first principles of fluid mechanics allow an accurate verification of the CSF flow patters for individual patients. This paper presents a detailed analysis of pulsatile CSF flow and pressure dynamics in a normal and hydrocephalic patient. Experimental CSF flow measurements and computational results of flow and pressure fields in the ventricular system, the SAS and brain parenchyma are presented. The pulsating CSF motion is explored in normal and pathological conditions of communicating hydrocephalus. This paper predicts small transmantle pressure differences between lateral ventricles and SASs (approximately 10 Pa). The transmantle pressure between ventricles and SAS remains small even in the hydrocephalic patient (approximately 30 Pa), but the ICP pulsatility increases by a factor of four. The computational fluid dynamics (CFD) results of the predicted CSF flow velocities are in good agreement with Cine MRI measurements. Differences between the predicted and observed CSF flow velocities in the prepontine area point towards complex brain-CSF interactions. The paper presents the complete computational model to predict the pulsatile CSF flow in the cranial cavity.