A*STAR-NUS Clinical Imaging Research Centre

A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological "atoms". Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in vivo human cortical parcellation. Almost all previous parcellations relied on 1 of 2 approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here, we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than 4 previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured subareal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multiresolution parcellations generated from 1489 participants are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal).

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Abstract A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) offers the possibility of in-vivo human cortical parcellation. Almost all previous parcellations relied on one of two approaches. The local gradient approach detects abrupt transitions in functional connectivity patterns. These transitions potentially reflect cortical areal boundaries defined by histology or visuotopic fMRI. By contrast, the global similarity approach clusters similar functional connectivity patterns regardless of spatial proximity, resulting in parcels with homogeneous (similar) rs-fMRI signals. Here we propose a gradient-weighted Markov Random Field (gwMRF) model integrating local gradient and global similarity approaches. Using task-fMRI and rs-fMRI across diverse acquisition protocols, we found gwMRF parcellations to be more homogeneous than four previously published parcellations. Furthermore, gwMRF parcellations agreed with the boundaries of certain cortical areas defined using histology and visuotopic fMRI. Some parcels captured sub-areal (somatotopic and visuotopic) features that likely reflect distinct computational units within known cortical areas. These results suggest that gwMRF parcellations reveal neurobiologically meaningful features of brain organization and are potentially useful for future applications requiring dimensionality reduction of voxel-wise fMRI data. Multi-resolution parcellations generated from 1489 participants are available ( https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal )

Growing interest in extracellular vesicles (EVs, including exosomes and microvesicles) as therapeutic entities, particularly in stem cell-related approaches, has underlined the need for standardization and coordination of development efforts. Members of the International Society for Extracellular Vesicles and the Society for Clinical Research and Translation of Extracellular Vesicles Singapore convened a Workshop on this topic to discuss the opportunities and challenges associated with development of EV-based therapeutics at the preclinical and clinical levels. This review outlines topic-specific action items that, if addressed, will enhance the development of best-practice models for EV therapies. Stem Cells Translational Medicine 2017;6:1730-1739.

We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminar-specific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain.

UNLABELLED: Evaluation of tumor heterogeneity based on texture parameters has recently attracted much interest in the PET imaging community. However, the impact of reconstruction settings on texture parameters is unclear, especially relating to time-of-flight and point-spread function modeling. Their effects on 55 texture features (TFs) and 6 features based on first-order statistics (FOS) were investigated. Standardized uptake value (SUV) measures were also evaluated as peak SUV (SUVpeak), maximum SUV, and mean SUV (SUVmean). METHODS: This study retrospectively recruited 20 patients with lesions in the lung who underwent whole-body (18)F-FDG PET/CT. The coefficient of variation (COV) of each feature across different reconstructions was calculated. RESULTS: SUVpeak, SUVmean, 18 TFs, and 1 FOS were the most robust (COV ≤ 5%) whereas skewness, cluster shade, and zone percentage were the least robust (COV > 20%) with respect to reconstruction algorithms using default settings. Heterogeneity parameters had different sensitivities to iteration number. Twenty-four parameters including SUVpeak and SUVmean exhibited variation with a COV less than 5%; 28 parameters, including maximum SUV, showed variation with a COV in the range of 5%-10%. In addition, skewness, cluster shade, and zone percentage were the most sensitive to iteration number. In terms of sensitivity to full width at half maximum (FWHM), 15 TFs and 1 FOS had the best performance with a COV less than 5%, whereas SUVpeak and SUVmean had a COV between 5% and 10%. Grid size had the largest impact on image features, which was demonstrated by only 11 features, including SUVpeak and SUVmean, having a COV less than 10%. CONCLUSION: Different image features have different sensitivities to reconstruction settings. Iteration number and FWHM of the gaussian filter have a similar impact on the image features. Grid size has a larger impact on the features than iteration number and FWHM. The features that exhibited large variations such as skewness in FOS, cluster shade, and zone percentage should be used with caution. The entropy in FOS, difference entropy, inverse difference normalized, inverse difference moment normalized, low gray-level run emphasis, high gray-level run emphasis, and low gray-level zone emphasis are the most robust features.

gene, for which there is currently no cure. The identification of sensitive indicators of disease progression and therapeutic outcome could help the development of effective strategies for treating HD. We assessed mutant huntingtin (mHTT) and neurofilament light (NfL) protein concentrations in cerebrospinal fluid (CSF) and blood in parallel with clinical evaluation and magnetic resonance imaging in premanifest and manifest HD mutation carriers. Among HD mutation carriers, NfL concentrations in plasma and CSF correlated with all nonbiofluid measures more closely than did CSF mHTT concentration. Longitudinal analysis over 4 to 8 weeks showed that CSF mHTT, CSF NfL, and plasma NfL concentrations were highly stable within individuals. In our cohort, concentration of CSF mHTT accurately distinguished between controls and HD mutation carriers, whereas NfL concentration, in both CSF and plasma, was able to segregate premanifest from manifest HD. In silico modeling indicated that mHTT and NfL concentrations in biofluids might be among the earliest detectable alterations in HD, and sample size prediction suggested that low participant numbers would be needed to incorporate these measures into clinical trials. These findings provide evidence that biofluid concentrations of mHTT and NfL have potential for early and sensitive detection of alterations in HD and could be integrated into both clinical trials and the clinic.

A complex system can be represented and analyzed as a network, where nodes represent the units of the network and edges represent connections between those units. For example, a brain network represents neurons as nodes and axons between neurons as edges. In many networks, some nodes have a disproportionately high number of edges as well as many edges between each other and are referred to as the "rich club". In many different networks, the nodes of this club are assumed to support global network integration. Here we show that another set of nodes, which have edges diversely distributed across the network, form a "diverse club". The diverse club exhibits, to a greater extent than the rich club, properties consistent with an integrative network function-these nodes are more highly interconnected and their edges are more critical for efficient global integration. Finally, these two clubs potentially evolved via distinct selection pressures.

AIMS: Rupture-prone atherosclerotic plaques are characterized by inflammation and a large necrotic core. Inflammation is linked to high metabolic activity. Advanced glycation endproducts (AGEs) and their major precursor methylglyoxal are formed during high metabolic activity and can have detrimental effects on cellular function and may induce cell death. Therefore, we investigated whether plaque AGEs are increased in human carotid rupture-prone plaques and are associated with plaque inflammation and necrotic core formation. METHODS AND RESULTS: The protein-bound major methylglyoxal-derived AGE 5-hydro-5-methylimidazolone (MG-H1) and N(ε)-(carboxymethyl)lysine (CML) were measured in human carotid endarterectomy specimens (n = 75) with tandem mass spectrometry. MG-H1 and CML levels were associated with rupture-prone plaques, increased protein levels of the inflammatory mediators IL-8 and MCP-1 and with higher MMP-9 activity. Immunohistochemistry showed that AGEs accumulated predominantly in macrophages surrounding the necrotic core and co-localized with cleaved caspase-3. Intra-plaque comparison revealed that glyoxalase-1 (GLO-1), the major methylglyoxal-detoxifying enzyme, mRNA was decreased (-13%, P < 0.05) in ruptured compared with stable plaque segments. In line, in U937 monoctyes, we found reduced (GLO-1) activity (-38%, P < 0.05) and increased MGO (346%, P < 0.05) production after stimulation with the inflammatory mediator TNF. Direct incubation with methylglyoxal increased apoptosis up to two-fold. CONCLUSION: This is the first study showing that AGEs are associated with human rupture-prone plaques. Furthermore, this study suggests a cascade linking inflammation, reduced GLO-1, methylglyoxal- and AGE-accumulation, and subsequent apoptosis. Thereby, AGEs may act as mediators of the progression of stable to rupture-prone plaques, opening a window towards novel treatments and biomarkers to treat cardiovascular diseases.

ICF syndrome (immunodeficiency, centromere instability and facial anomalies) is a recessive human genetic disorder resulting from mutations in the DNA methyltransferase 3B (DNMT3B) gene. Patients with this disease exhibit numerous chromosomal abnormalities, including anomalous decondensation, pairing, separation and breakage, primarily involving the pericentromeric regions of chromosomes 1 and 16. Global levels of DNA methylation in ICF cells are only slightly reduced; however, certain repetitive sequences and genes on the inactive X chromosome of female ICF patients are significantly hypomethylated. In the present report, we analyze the molecular defect of de novo methylation in ICF cells in greater detail by making use of a model Epstein-Barr virus (EBV)-based system and three members of the unique cellular cancer-testis (C-T) gene family. Results with the EBV-based system indicate that de novo methylation of newly introduced viral sequences is defective in ICF syndrome. Limited de novo methylation capacity is retained in ICF cells, indicating that the mutations in DNMT3B are not complete loss-of-function mutations or that other DNMTs cooperate with DNMT3B. Analysis of three C-T genes (two on the X chromosome and one autosomal) revealed that loss of methylation from cellular gene sequences is heterogeneous, with both autosomal and X chromosome-based genes demonstrating sensitivity to mutations in DNMT3B. Aberrant hypomethylation at a number of loci examined correlated with altered gene expression levels. Lastly, no consistent changes in the protein levels of the DNA methyltransferases were noted when normal and ICF cell lines were compared.

Advanced intelligent embedded systems perform cognitive tasks with highly-efficient vector-processing units for deep neural network (DNN) inference and other vector-based signal processing using limited power. SRAM-based compute-in-memory (CIM) achieves high energy efficiency for vector-matrix multiplications, offers <1ns read/write speed, and saves vastly repeating memory accesses. However, prior SRAM CIM macros require a large area for compute circuits (either using ADC for analog CIM [1– 4] or CMOS static logic for all-digital CIM [5–6]), have limited CIM functions, and use fixed vector-processing dimensions that cause a low-spatial-utilization rate when deploying DNN (Fig. 11.7.1).

The results of most neuroimaging studies are reported in volumetric (e.g., MNI152) or surface (e.g., fsaverage) coordinate systems. Accurate mappings between volumetric and surface coordinate systems can facilitate many applications, such as projecting fMRI group analyses from MNI152/Colin27 to fsaverage for visualization or projecting resting-state fMRI parcellations from fsaverage to MNI152/Colin27 for volumetric analysis of new data. However, there has been surprisingly little research on this topic. Here, we evaluated three approaches for mapping data between MNI152/Colin27 and fsaverage coordinate systems by simulating the above applications: projection of group-average data from MNI152/Colin27 to fsaverage and projection of fsaverage parcellations to MNI152/Colin27. Two of the approaches are currently widely used. A third approach (registration fusion) was previously proposed, but not widely adopted. Two implementations of the registration fusion (RF) approach were considered, with one implementation utilizing the Advanced Normalization Tools (ANTs). We found that RF-ANTs performed the best for mapping between fsaverage and MNI152/Colin27, even for new subjects registered to MNI152/Colin27 using a different software tool (FSL FNIRT). This suggests that RF-ANTs would be useful even for researchers not using ANTs. Finally, it is worth emphasizing that the most optimal approach for mapping data to a coordinate system (e.g., fsaverage) is to register individual subjects directly to the coordinate system, rather than via another coordinate system. Only in scenarios where the optimal approach is not possible (e.g., mapping previously published results from MNI152 to fsaverage), should the approaches evaluated in this manuscript be considered. In these scenarios, we recommend RF-ANTs (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/registration/Wu2017_RegistrationFusion).

Healthy aging is accompanied by disruptions in the functional modular organization of the human brain. Cross-sectional studies have shown age-related reductions in the functional segregation and distinctiveness of brain networks. However, less is known about the longitudinal changes in brain functional modular organization and their associations with aging-related cognitive decline. We examined age-and aging-related changes in functional architecture of the cerebral cortex using a dataset comprising a cross-sectional healthy young cohort of 57 individuals (mean SD age, 23.71 3.61 years, 22 males) and a longitudinal healthy elderly cohort of 72 individuals (mean baseline age, 68.22 5.80 years, 39 males) with 2-3 time points (18 -24 months apart) of task-free fMRI data. We found both cross-sectional (elderly vs young) and longitudinal (in elderly) global decreases in network segregation (decreased local efficiency), integration (decreased global efficiency), and module distinctiveness (increased participation coefficient and decreased system segregation). At the modular level, whereas cross-sectional analyses revealed higher participation coefficient across all modules in the elderly compared with young participants, longitudinal analyses revealed focal longitudinal participation coefficient increases in three higherorder cognitive modules: control network, default mode network, and salience/ventral attention network. Cross-sectionally, elderly participants also showed worse attention performance with lower local efficiency and higher mean participation coefficient, and worse global cognitive performance with higher participation coefficient in the dorsal attention/control network. These findings suggest that healthy aging is associated with whole-brain connectome-wide changes in the functional modular organization of the brain, accompanied by loss of functional segregation, particularly in higher-order cognitive networks.

BACKGROUND: Yttrium-90 (90Y) positron emission tomography with integrated computed tomography (PET/CT) represents a technological leap from 90Y bremsstrahlung single-photon emission computed tomography with integrated computed tomography (SPECT/CT) by coincidence imaging of low abundance internal pair production. Encouraged by favorable early experiences, we implemented post-radioembolization 90Y PET/CT as an adjunct to 90Y bremsstrahlung SPECT/CT in diagnostic reporting. METHODS: This is a retrospective review of all paired 90Y PET/CT and 90Y bremsstrahlung SPECT/CT scans over a 1-year period. We compared image resolution, ability to confirm technical success, detection of non-target activity, and providing conclusive information about 90Y activity within targeted tumor vascular thrombosis. 90Y resin microspheres were used. 90Y PET/CT was performed on a conventional time-of-flight lutetium-yttrium-oxyorthosilicate scanner with minor modifications to acquisition and reconstruction parameters. Specific findings on 90Y PET/CT were corroborated by 90Y bremsstrahlung SPECT/CT, 99mTc macroaggregated albumin SPECT/CT, follow-up diagnostic imaging or review of clinical records. RESULTS: Diagnostic reporting recommendations were developed from our collective experience across 44 paired scans. Emphasis on the continuity of care improved overall diagnostic accuracy and reporting confidence of the operator. With proper technique, the presence of background noise did not pose a problem for diagnostic reporting. A counter-intuitive but effective technique of detecting non-target activity is proposed, based on the pattern of activity and its relation to underlying anatomy, instead of its visual intensity. In a sub-analysis of 23 patients with a median follow-up of 5.4 months, 90Y PET/CT consistently outperformed 90Y bremsstrahlung SPECT/CT in all aspects of qualitative analysis, including assessment for non-target activity and tumor vascular thrombosis. Parts of viscera closely adjacent to the liver remain challenging for non-target activity detection, compounded by a tendency for mis-registration. CONCLUSIONS: Adherence to proper diagnostic reporting technique and emphasis on continuity of care are vital to the clinical utility of post-radioembolization 90Y PET/CT. 90Y PET/CT is superior to 90Y bremsstrahlung SPECT/CT for the assessment of target and non-target activity.

Fetal pain has long been a contentious issue, in large part because fetal pain is often cited as a reason to restrict access to termination of pregnancy or abortion. We have divergent views regarding the morality of abortion, but have come together to address the evidence for fetal pain. Most reports on the possibility of fetal pain have focused on developmental neuroscience. Reports often suggest that the cortex and intact thalamocortical tracts are necessary for pain experience. Given that the cortex only becomes functional and the tracts only develop after 24 weeks, many reports rule out fetal pain until the final trimester. Here, more recent evidence calling into question the necessity of the cortex for pain and demonstrating functional thalamic connectivity into the subplate is used to argue that the neuroscience cannot definitively rule out fetal pain before 24 weeks. We consider the possibility that the mere experience of pain, without the capacity for self reflection, is morally significant. We believe that fetal pain does not have to be equivalent to a mature adult human experience to matter morally, and so fetal pain might be considered as part of a humane approach to abortion.

BACKGROUND: Lowering injected dose will have an effect on PET image quality. In this article, we aim to investigate this effect in terms of signal-to-noise ratio (SNR) in the liver, contrast-to-noise ratio (CNR) in the lesion, bias and ensemble image noise. METHODS: We present here our method and preliminary results using tuberculosis (TB) cases. Sixteen patients who underwent (18)F-FDG PET/MR scans covering the whole lung and portion of the liver were selected for the study. Reduced doses were simulated by randomly discarding events in the PET list mode data stream, and ten realizations at each simulated dose were generated and reconstructed. The volumes of interest (VOI) were delineated on the image reconstructed from the original full statistics data for each patient. Four thresholds (20, 40, 60 and 80 % of SUVmax) were used to quantify the effect of the threshold on CNR at the different count level. Image metrics were calculated for each VOI. This experiment allowed us to quantify the loss of SNR and CNR as a function of the counts in the scan, in turn related to dose injected. Reproducibility of mean and maximum standardized uptake value (SUVmean and SUVmax) measurement in the lesions was studied as standard deviation across 10 realizations. RESULTS: At 5 × 10(6) counts in the scan, the average SNR in the liver in the observed samples is about 3, and the CNR is reduced to 60 % of the full statistics value. The CNR in the lesion and SNR in the liver decreased with reducing count data. The variation of CNR across the four thresholds does not significantly change until the count level of 5 × 10(6). After correcting the factor related to subject's weight, the square of the SNR in the liver was found to have a very good linear relationship with detected counts. Some quantitative bias appears with count reduction. At the count level of 5 × 10(6), bias and noise in terms of SUVmean and SUVmax are up to 10 and 20 %, respectively. To keep both bias and noise less than 10 %, 5 × 10(6) counts and 20 × 10(6) counts were required for SUVmean and SUVmax, respectively. CONCLUSIONS: Initial results with the given data of 16 patients diagnosed as TB demonstrated that 5 × 10(6) counts in the scan could be sufficient to yield good images in terms of SNR, CNR, bias and noise. In the future, more work needs to be done to validate the proposed method with a larger population and lung cancer patient data.

UNLABELLED: The pathogenesis of type 2 diabetes is characterized by impaired insulin action and increased hepatic glucose production (HGP). Despite the importance of hepatic metabolic aberrations in diabetes development, there is currently no molecular probe that allows measurement of hepatic gluconeogenic pathways in vivo and in a noninvasive manner. In this study, we used hyperpolarized carbon 13 ((13)C)-labeled pyruvate magnetic resonance spectroscopy (MRS) to determine changes in hepatic gluconeogenesis in a high-fat diet (HFD)-induced mouse model of type 2 diabetes. Compared with mice on chow diet, HFD-fed mice displayed higher levels of oxaloacetate, aspartate, and malate, along with increased (13)C label exchange rates between hyperpolarized [1-(13) C]pyruvate and its downstream metabolites, [1-(13)C]malate and [1-(13)C]aspartate. Biochemical assays using liver extract revealed up-regulated malate dehydrogenase activity, but not aspartate transaminase activity, in HFD-fed mice. Moreover, the (13) C label exchange rate between [1-(13)C]pyruvate and [1-(13)C]aspartate (k(pyr->asp)) exhibited apparent correlation with gluconeogenic pyruvate carboxylase (PC) activity in hepatocytes. Finally, up-regulated HGP by glucagon stimulation was detected by an increase in aspartate signal and k(pyr->asp), whereas HFD mice treated with metformin for 2 weeks displayed lower production of aspartate and malate, as well as reduced k(pyr->asp) and (13)C-label exchange rate between pyruvate and malate, consistent with down-regulated gluconeogenesis. CONCLUSION: Taken together, we demonstrate that increased PC flux is an important pathway responsible for increased HGP in diabetes development, and that pharmacologically induced metabolic changes specific to the liver can be detected in vivo with a hyperpolarized (13)C-biomolecular probe. Hyperpolarized (13)C MRS and the determination of metabolite exchange rates may allow longitudinal monitoring of liver function in disease development.

Time-of-flight (TOF) and point spread function (PSF) modeling have been shown to improve PET reconstructions, but the impact on physicians in the clinical setting has not been thoroughly investigated. A lesion detection and localization study was performed using simulated lesions in real patient images. Four reconstruction schemes were considered: ordinary Poisson OSEM (OP) alone and combined with TOF, PSF, and TOF + PSF. The images were presented to physicians experienced in reading PET images, and the performance of each was quantified using localization receiver operating characteristic. Numerical observers (non-prewhitening and Hotelling) were used to identify optimal reconstruction parameters, and observer SNR was compared to the performance of the physicians. The numerical models showed good agreement with human performance, and best performance was achieved by both when using TOF + PSF. These findings suggest a large potential benefit of TOF + PSF for oncology PET studies, especially in the detection of small, low-intensity, focal disease in larger patients.

Abstract Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 minutes) showed comparable generalizability as parcellations estimated by two state-of-the-art methods using five sessions (50 minutes). We also showed that behavioral phenotypes across cognition, personality and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength , individual-specific network topography might also serve as a fingerprint of human behavior.

In this work, we report a novel method of single step facile synthesis of magnetite nanoclusters via thermal decomposition of iron(III) acetylacetonate in a liquid mixture of tri(ethylene glycol) (TREG) and triethanolamine (TREA). The optimized ratio of TREG : TREA has been found to be 1 : 4 (v/v) for the formation of well dispersed MNC-14 magnetite nanoclusters with high Ms values (75 emu g−1) as compared to MNC-10 magnetite nanoparticles (63 emu g−1). The MNC-14 nanoclusters were found to be nontoxic to MCF-7 cells up to an iron concentration of 10 mg ml−1. The MNC-14 nanoclusters yielded high specific absorption rate (SAR) values (∼500 Watt g−1 at 89 kA m−1 AC magnetic field and 240 kHz frequency) and thus qualified for their possible use in magnetic hyperthermia treatment, while MNC-10 nanoparticles possess a much lower SAR value of 135 Watt g−1. In vitro magnetic hyperthermia experiments (using the MNC-14 nanoclusters with the iron concentration of 0.5 mg ml−1) showed about 74% loss in viability of MCF-7 breast cancer cells indicating that they are a very suitable candidate for magnetic hyperthermia treatment of cancer. The r2 and r2* relaxivity values of MNC-14 nanoclusters (294.99 and 450.05 s−1 mM−1) as measured by a 9.4 T MRI scanner were higher than those for the MNC-10 nanoparticles (205.6 and 309.2 s−1 mM−1). The MNC-14 nanoclusters also showed very promising in vivo tumor imaging. Thus, the newly synthesized novel MNC-14 nanoclusters possess great potential in clinical MRI and magnetic hyperthermia applications and may be used simultaneously for cancer diagnosis and therapy.