A preliminary choroid plexus volumetric study in individuals with psychosis.

The choroid plexus (ChP) is part of the blood-cerebrospinal fluid barrier, regulating brain homeostasis and the brain's response to peripheral events. Its upregulation and enlargement are considered essential in psychosis. However, the timing of the ChP enlargement has not been established. This study introduces a novel magnetic resonance imaging-based segmentation method to examine ChP volumes in two cohorts of individuals with psychosis. The first sample consists of 41 individuals with early course psychosis (mean duration of illness = 1.78 years) and 30 healthy individuals. The second sample consists of 30 individuals with chronic psychosis (mean duration of illness = 7.96 years) and 34 healthy individuals. We utilized manual segmentation to measure ChP volumes. We applied ANCOVAs to compare normalized ChP volumes between groups and partial correlations to investigate the relationship between ChP, LV volumes, and clinical characteristics. Our segmentation demonstrated good reliability (.87). We further showed a significant ChP volume increase in early psychosis (left: p < .00010, right: p < .00010) and a significant positive correlation between higher ChP and higher LV volumes in chronic psychosis (left: r = .54, p = .0030, right: r = .68; p < .0010). Our study suggests that ChP enlargement may be a marker of acute response around disease onset. It might also play a modulatory role in the chronic enlargement of lateral ventricles, often reported in psychosis. Future longitudinal studies should investigate the dynamics of ChP enlargement as a promising marker for novel therapeutic strategies.

Anatomically curated segmentation of human subcortical structures in high resolution magnetic resonance imaging: An open science approach.

Magnetic resonance imaging (MRI)-based brain segmentation has recently been revolutionized by deep learning methods. These methods use large numbers of annotated segmentations to train algorithms that have the potential to perform brain segmentations reliably and quickly. However, training data for these algorithms are frequently obtained from automated brain segmentation systems, which may contain inaccurate neuroanatomy. Thus, the neuroimaging community would benefit from an open source database of high quality, neuroanatomically curated and manually edited MRI brain images, as well as the publicly available tools and detailed procedures for generating these curated data. Manual segmentation approaches are regarded as the gold standard for brain segmentation and parcellation. These approaches underpin the construction of neuroanatomically accurate human brain atlases. In addition, neuroanatomically precise definitions of MRI-based regions of interest (ROIs) derived from manual brain segmentation are essential for accuracy in structural connectivity studies and in surgical planning for procedures such as deep brain stimulation. However, manual segmentation procedures are time and labor intensive, and not practical in studies utilizing very large datasets, large cohorts, or multimodal imaging. Automated segmentation methods were developed to overcome these issues, and provide high data throughput, increased reliability, and multimodal imaging capability. These methods utilize manually labeled brain atlases to automatically parcellate the brain into different ROIs, but do not have the anatomical accuracy of skilled manual segmentation approaches. In the present study, we developed a custom software module for manual editing of brain structures in the freely available 3D Slicer software platform that employs principles and tools based on pioneering work from the Center for Morphometric Analysis (CMA) at Massachusetts General Hospital. We used these novel 3D Slicer segmentation tools and techniques in conjunction with well-established neuroanatomical definitions of subcortical brain structures to manually segment 50 high resolution T1w MRI brains from the Human Connectome Project (HCP) Young Adult database. The structural definitions used herein are associated with specific neuroanatomical ontologies to systematically interrelate histological and MRI-based morphometric definitions. The resulting brain datasets are publicly available and will provide the basis for a larger database of anatomically curated brains as an open science resource.

The association of matrix metalloproteinase 9 (MMP9) with hippocampal volume in schizophrenia: a preliminary MRI study.

Matrix metalloproteinases 9 (MMP9) are enzymes involved in regulating neuroplasticity in the hippocampus. This, combined with evidence for disrupted hippocampal structure and function in schizophrenia, has prompted our current investigation into the relationship between MMP9 and hippocampal volumes in schizophrenia. 34 healthy individuals (mean age = 32.50, male = 21, female = 13) and 30 subjects with schizophrenia (mean age = 33.07, male = 19, female = 11) underwent a blood draw and T1-weighted magnetic resonance imaging. The hippocampus was automatically segmented utilizing FreeSurfer. MMP9 plasma levels were measured with ELISA. ANCOVAs were conducted to compare MMP9 plasma levels (corrected for age and sex) and hippocampal volumes between groups (corrected for age, sex, total intracranial volume). Spearman correlations were utilized to investigate the relationship between symptoms, medication, duration of illness, number of episodes, and MMP9 plasma levels in patients. Last, we explored the correlation between MMP9 levels and hippocampal volumes in patients and healthy individuals separately. Patients displayed higher MMP9 plasma levels than healthy individuals (F(1, 60) = 21.19, p < 0.0001). MMP9 levels correlated with negative symptoms in patients (R = 0.39, p = 0.035), but not with medication, duration of illness, or the number of episodes. Further, patients had smaller left (F(1,59) = 9.12, p = 0.0040) and right (F(1,59) = 6.49, p = 0.013) hippocampal volumes. Finally, left (R = -0.39, p = 0.034) and right (R = -0.37, p = 0.046) hippocampal volumes correlated negatively with MMP9 plasma levels in patients. We observe higher MMP9 plasma levels in SCZ, associated with lower hippocampal volumes, suggesting involvement of MMP9 in the pathology of SCZ. Future studies are needed to investigate how MMP9 influences the pathology of SCZ over the lifespan, whether the observed associations are specific for schizophrenia, and if a therapeutic modulation of MMP9 promotes neuroprotective effects in SCZ.

Microstructural alterations in medial forebrain bundle are associated with interindividual pain sensitivity.

The perception of pain to noxious stimuli, also known as pain sensitivity, varies among individuals. The comprised brain structures and their white matter pathways are complex and elusive. Here, we aimed to investigate whether variation of microstructure of the medial forebrain bundle (MFB), a tract connecting the basal forebrain with the brain stem, is associated with interindividual pain sensitivity. We assessed interindividual pain sensitivity as a rating of pain intensity to heat stimuli (45, 47, and 48.9°C) in 38 healthy men (age: 27.05 ± 5.7 years). We also reconstructed the MFB using multitensor tractography from diffusion magnetic resonance imaging (dMRI) and calculated free-water corrected dMRI measures of fractional anisotropy (FAt ), radial diffusivity (RDt ), and axial diffusivity (ADt ). Lower ratings of interindividual pain intensity correlated with higher FAt and lower RDt of the MFB. As changes in FAt and RDt may reflect abnormalities in myelination, the results might be interpreted as that a lower pain rating is associated with higher degree of myelination of the MFB and could represent an inhibitory pathway of pain. Our results suggest that alteration of microstructure in the MFB contributes to the interindividual variation of pain perception.

Improving Metabolic Pathway Efficiency by Statistical Model-Based Multivariate Regulatory Metabolic Engineering.

Metabolic engineering entails target modification of cell metabolism to maximize the production of a specific compound. For empowering combinatorial optimization in strain engineering, tools and algorithms are needed to efficiently sample the multidimensional gene expression space and locate the desirable overproduction phenotype. We addressed this challenge by employing design of experiment (DoE) models to quantitatively correlate gene expression with strain performance. By fractionally sampling the gene expression landscape, we statistically screened the dominant enzyme targets that determine metabolic pathway efficiency. An empirical quadratic regression model was subsequently used to identify the optimal gene expression patterns of the investigated pathway. As a proof of concept, our approach yielded the natural product violacein at 525.4 mg/L in shake flasks, a 3.2-fold increase from the baseline strain. Violacein production was further increased to 1.31 g/L in a controlled benchtop bioreactor. We found that formulating discretized gene expression levels into logarithmic variables (Linlog transformation) was essential for implementing this DoE-based optimization procedure. The reported methodology can aid multivariate combinatorial pathway engineering and may be generalized as a standard procedure for accelerating strain engineering and improving metabolic pathway efficiency.