Neurite imaging reveals microstructural variations in human cerebral cortical gray matter

We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture

The importance of clinical and labour market histories in psychiatric disability retirement : analysis of the comprehensive Finnish national-level RETIRE data

Objectives Despite the stable incidence of mental disorders in Finland and Europe, mental health-related occupational disability has been increasing. We unveiled the paths to permanent psychiatric disability, recovery, or death, by analysing sequences of labour market participation. Methods The RETIRE register database includes information regarding all persons (n = 42,170) awarded an ICD-10 psychiatric disability pension between 2010 and 2015 in Finland. We identified clusters of typical paths of pre-retirement labour market history. Controlling for major mental disorders, age, and sex, we evaluated factors associated with returning to work (RTW), or death, over a 5-year follow-up period. Results Only 10.5% of the disabled subjects returned to work within the follow-up. Half of them ended up with a permanent disability pension. Seven distinguishable paths to disability were identified. Subjects in the cluster characterized by steady employment were relatively often females, lost their work ability due to affective disorders, and had the highest rate of returning to work (16.3%). Mortality was highest (9%) among the cluster characterized by long-term unemployment. Distributions of major diagnostic groups, as well as age and sex, differed between clusters. After their adjustment in the analysis of RTW or death, the identified labour market history paths prior to losing work ability remained as important independent prognostic factors for both outcomes. Conclusions The complex retirement process involves identifiable clinical and contextual associating factors. Labour market history patterns associate with varying prognoses after psychiatric retirement. Prolonged unemployment appears as a predictor of relatively poor prognoses, whereas employment indicates the opposite.Peer reviewe

The effects of drainage and restoration of pine mires on habitat structure, vegetation and ants

Habitat loss and degradation are the main threats to biodiversity worldwide. For example, nearly 80% of peatlands in southern Finland have been drained. There is thus a need to safeguard the remaining pristine mires and to restore degraded ones. Ants play a pivotal role in many ecosystems and like many keystone plant species, shape ecosystem conditions for other biota. The effects of mire restoration and subsequent vegetation succession on ants, however, are poorly understood. We inventoried tree stands, vegetation, water-table level, and ants (with pitfall traps) in nine mires in southern Finland to explore differences in habitats, vegetation and ant assemblages among pristine, drained (30-40 years ago) and recently restored (1-3 years ago) pine mires. We expected that restoring the water-table level by ditch filling and reconstructing sparse tree stands by cuttings will recover mire vegetation and ants. We found predictable responses in habitat structure, floristic composition and ant assemblage structure both to drainage and restoration. However, for mire-specialist ants the results were variable and longer-term monitoring is needed to confirm the success of restoration since these social insects establish perennial colonies with long colony cycles. We conclude that restoring the water-table level and tree stand structure seem to recover the characteristic vegetation and ant assemblages in the short term. This recovery was likely enhanced because drained mires still had both acrotelm and catotelm, and connectedness was still reasonable for mire organisms to recolonize the restored mires either from local refugia or from populations of nearby mires.Peer reviewe

Towards HCP-style macaque connectomes: 24-channel 3T multi-array coil, MRI sequences and preprocessing

Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain

A Strategy For Identifying Putative Causes Of Gene Expression Variation In Human Cancer

There is often a need to predict the impact of alterations in one variable on another variable. This is especially the case in cancer research, where much effort has been made to carry out large-scale gene expression screening by microarray techniques. However, the causes of this variability from one cancer to another and from one gene to another often remain unknown. In this study we present a systematic procedure for finding genes whose expression is altered by an intrinsic or extrinsic explanatory phenomenon. The procedure has three stages: preprocessing, data integration and statistical analysis. We tested and verified the utility of this approach in a study, where expression and copy number of 13,824 genes were determined in 14 breast cancer samples. The expression of 270 genes could be explained by the variability of gene copy number. These genes may represent an important set of primary, genetically "damaged" genes that drive cancer progression

Characterisation of the course of Mycoplasma bovis infection in naturally infected dairy herds

Mycoplasma bovis causes bovine respiratory disease, mastitis, arthritis and otitis. The importance of M. bovis has escalated because of recent outbreaks and introductions into countries previously free of M. bovis. We characterized the course of M. bovis infection on 19 recently infected dairy farms over 24 months. Our objective was to identify diagnostic tools to assess the efficacy of control measures to assess low risk infection status on M. bovis infected farms. PCR assays and culture were used to detect M. bovis, and in-house and BioX ELISAs were used to follow antibody responses. Cows and young stock were sampled on four separate occasions, and clinical cases were sampled when they arose. On 17 farms, a few cases of clinical mastitis were detected, mostly within the first eight weeks after the index case. Antibodies detected by in-house ELISA persisted in the serum of cows at least for 1.5 years on all farms, regardless of the M. bovis infection status or signs of clinical disease or subclinical mastitis on the farm. Six out of 19 farms became low risk as the infection was resolved. Our results suggest that, for biosecurity purposes, regular monitoring should be conducted on herds by screening for M. bovis in samples from cows with clinical mastitis and calves with pneumonia, in conjunction with testing young stock by screening longitudinally collected nasal swabs for M. bovis and sequential serum samples for antibody against recombinant antigen.Peer reviewe

On the Adaptive Partition Approach to the Detection of Multiple Change-Points

With an adaptive partition procedure, we can partition a “time course” into consecutive non-overlapped intervals such that the population means/proportions of the observations in two adjacent intervals are significantly different at a given level . However, the widely used recursive combination or partition procedures do not guarantee a global optimization. We propose a modified dynamic programming algorithm to achieve a global optimization. Our method can provide consistent estimation results. In a comprehensive simulation study, our method shows an improved performance when it is compared to the recursive combination/partition procedures. In practice, can be determined based on a cross-validation procedure. As an application, we consider the well-known Pima Indian Diabetes data. We explore the relationship among the diabetes risk and several important variables including the plasma glucose concentration, body mass index and age