Brain temperature regulation in poor-grade subarachnoid hemorrhage patients – A multimodal neuromonitoring study

Elevated body temperature (T_core) is associated with poor outcome after subarachnoid hemorrhage (SAH). Brain temperature (T_brain) is usually higher than T_core. However, the implication of this difference (T_delta) remains unclear. We aimed to study factors associated with higher T_delta and its association with outcome. We included 46 SAH patients undergoing multimodal neuromonitoring, for a total of 7879 h of averaged data of T_core, T_brain, cerebral blood flow, cerebral perfusion pressure, intracranial pressure and cerebral metabolism (CMD). Three-months good functional outcome was defined as modified Rankin Scale ≤2. T_brain was tightly correlated with T_core (r = 0.948, p < 0.01), and was higher in 73.7% of neuromonitoring time (T_delta +0.18°C, IQR −0.01 – 0.37°C). A higher T_delta was associated with better metabolic state, indicated by lower CMD-glutamate (p = 0.003) and CMD-lactate (p < 0.001), and lower risk of mitochondrial dysfunction (MD) (OR = 0.2, p < 0.001). During MD, T_delta was significantly lower (0°C, IQR −0.2 – 0.1; p < 0.001). A higher T_delta was associated with improved outcome (OR = 7.7, p = 0.002). Our study suggests that T_brain is associated with brain metabolic activity and exceeds T_core when mitochondrial function is preserved. Further studies are needed to understand how T_delta may serve as a surrogate marker for brain function and predict clinical course and outcome after SAH.     

Clinical outcomes following proton therapy for adult craniopharyngioma: a single-institution cohort study

Journal of Neuro-Oncology - Craniopharyngioma is a benign tumor that commonly develops within the suprasellar region. The tumor and treatment can have debilitating consequences for pediatric and...     

Neuroarchitecture of the central complex of the desert locust: Tangential neurons

The central complex (CX) comprises a group of midline neuropils in the insect brain, consisting of the protocerebral bridge (PB), the upper (CBU) and lower division (CBL) of the central body and a pair of globular noduli. It receives prominent input from the visual system and plays a major role in spatial orientation of the animals. Vertical slices and horizontal layers of the CX are formed by columnar, tangential, and pontine neurons. While pontine and columnar neurons have been analyzed in detail, especially in the fruit fly and desert locust, understanding of the organization of tangential cells is still rudimentary. As a basis for future functional studies, we have studied the morphologies of tangential neurons of the CX of the desert locust Schistocerca gregaria. Intracellular dye injections revealed 43 different types of tangential neuron, 8 of the PB, 5 of the CBL, 24 of the CBU, 2 of the noduli, and 4 innervating multiple substructures. Cell bodies of these neurons were located in 11 different clusters in the cell body rind. Judging from the presence of fine versus beaded terminals, the vast majority of these neurons provide input into the CX, especially from the lateral complex (LX), the superior protocerebrum, the posterior slope, and other surrounding brain areas, but not directly from the mushroom bodies. Connections are largely subunit- and partly layer-specific. No direct connections were found between the CBU and the CBL. Instead, both subdivisions are connected in parallel with the PB and distinct layers of the noduli.     

The role of BDNF methylation and Val66Met in amygdala reactivity during emotion processing

Epigenetic alterations of the brain‐derived neurotrophic factor (BDNF) gene have been associated with psychiatric disorders in humans and with differences in amygdala BDNF mRNA levels in rodents. This human study aimed to investigate the relationship between the functional BDNF‐Val⁶⁶Met polymorphism, its surrounding DNA methylation in BDNF exon IX, amygdala reactivity to emotional faces, and personality traits. Healthy controls (HC, n = 189) underwent functional MRI during an emotional face‐matching task. Harm avoidance, novelty seeking and reward dependence were measured using the Tridimensional Personality Questionnaire (TPQ). Individual BDNF methylation profiles were ascertained and associated with several BDNF single nucleotide polymorphisms surrounding the BDNF‐Val⁶⁶Met, amygdala reactivity, novelty seeking and harm avoidance. Higher BDNF methylation was associated with higher amygdala reactivity (x = 34, y = 0, z = ?26, t₍₁₆₆₎ = 3.00, TFCE = 42.39, p_(FWE) = .045), whereby the BDNF‐Val⁶⁶Met genotype per se did not show any significant association with brain function. Furthermore, novelty seeking was negatively associated with BDNF methylation (r = ?.19, p = .015) and amygdala reactivity (r = ?.17, p = .028), while harm avoidance showed a trend for a positive association with BDNF methylation (r = .14, p = .066). The study provides first insights into the relationship among BDNF methylation, BDNF genotype, amygdala reactivity and personality traits in humans, highlighting the multidimensional relations among genetics, epigenetics, and neuronal functions. The present study suggests a possible involvement of epigenetic BDNF modifications in psychiatric disorders and related brain functions, whereby high BDNF methylation might reduce BDNF mRNA expression and upregulate amygdala reactivity.     

Physiological in vitro sacroiliac joint motion: a study on three‐dimensional posterior pelvic ring kinematics

The sacroiliac joint (SIJ) is a well‐known source of low back and pelvic pain, of increasing interest for both conservative and surgical treatment. Alterations in the kinematics of the pelvis have been hypothesized as a major cause of SIJ‐related pain. However, definitions of both the range and the extent of physiological movement are controversial, and there are no clear baseline data for pathological alterations. The present study combined a novel biomechanical setup allowing for physiological motion of the lumbosacral transition and pelvis without restricting the SIJ movement in vitro, combined with optical image correlation. Six fresh human pelvises (81 ± 10 years, three females, three males) were tested, with bodyweight‐adapted loading applied to the fifth lumbar vertebra and both acetabula. Deformation at the lumbopelvises was determined computationally from three‐dimensional image correlation data. Sacroiliac joint motion under the loading of 100% bodyweight primarily consisted of a z‐axis rotation (0.16°) and an inferior translation of the sacrum relative to the ilium (0.32 mm). Sacroiliac joint flexion‐extension rotations were minute (< 0.02°). Corresponding movements of the SIJ were found at the lumbosacral transition, with an anterior translation of L5 relative to the sacrum of ?0.97 mm and an inferior translation of 0.11 mm, respectively. Moreover, a flexion of 1.82° was observed at the lumbosacral transition. Within the innominate bone and at the pubic symphysis, small complementary rotations were seen around a vertical axis, accounting for ?0.10° and 0.11°, respectively. Other motions were minute and accompanied by large interindividual variation. The present study provides evidence of different SIJ motions than reported previously when exerted by physiological loading. Sacroiliac joint kinematics were in the sub‐degree and sub‐millimeter range, in line with previous in vivo and in vitro findings, largely limited to the sagittal rotation and an inferior translation of the sacrum relative to the ilium. This given physiological loading scenario underlines the relevance of the lumbosacral transition when considering the overall motion of the lumbopelvis, and how relatively little the other segments contribute to overall motion.     

MANIA—A Pattern Classification Toolbox for Neuroimaging Data

Conventional univariate statistics are common and widespread in neuroimaging research. However, functional and structural MRI data reveal a multivariate nature, since neighboring voxels are highly correlated and different localized brain regions activate interdependently. Multivariate pattern classification techniques are capable of overcoming shortcomings of univariate statistics. A rising interest in such approaches on neuroimaging data leads to an increasing demand of appropriate software and tools in this field. Here, we introduce and release MANIA—Machine learning Application for NeuroImaging Analyses. MANIA is a Matlab based software toolbox enabling easy pattern classification of neuroimaging data and offering a broad assortment of machine learning algorithms and feature selection methods. Between groups classifications are the main scope of this software, for instance the differentiation between patients and controls. A special emphasis was placed on an intuitive and easy to use graphical user interface allowing quick implementation and guidance also for clinically oriented researchers. MANIA is free and open source, published under GPL3 license. This work will give an overview regarding the functionality and the modular software architecture as well as a comparison between other software packages.