Cytoarchitectonic and chemoarchitectonic characterization of the prefrontal cortical areas in the mouse

This study describes cytoarchitectonic criteria to define the prefrontal cortical areas in the mouse brain (C57BL/6 strain). Currently, well-illustrated mouse brain stereotaxic atlases are available, which, however, do not provide a description of the distinctive cytoarchitectonic characteristics of individual prefrontal areas. Such a description is of importance for stereological, neuronal tracing, and physiological, molecular and neuroimaging studies in which a precise parcellation of the prefrontal cortex (PFC) is required. The present study describes and illustrates: the medial prefrontal areas, i.e., the infralimbic, prelimbic, dorsal and ventral anterior cingulate and Fr2 area; areas of the lateral PFC, i.e., the dorsal agranular insular cortical areas and areas of the ventral PFC, i.e., the lateral, ventrolateral, ventral and medial orbital areas. Each cytoarchitectonically defined boundary is corroborated by one or more chemoarchitectonic stainings, i.e., acetylcholine esterase, SMI32, SMI311, dopamine, parvalbumin, calbindin and myelin staining

Розрахунок та проектування окремого фундаменту будівлі на природній ґрунтовій основі. Методичні рекомендації до виконання практичних завдань та курсового проекту з дисципліни «Механіка ґрунтів, основи і фундаменти» сту- дентами напрямів підготовки 6.060101 Будівництво та 6.050301 Гірництво

Подано методичні рекомендації до виконання практичних завдань та кур- сового проекту з дисципліни «Механіка ґрунтів, основи і фундаменти» для сту- дентів напрямів підготовки 6.060101 Будівництво та 6.050301 Гірництво. Розглянуто порядок проектування фундаменту будівлі мілкого закладан- ня на природній ґрунтовій основі. Методичні рекомендації передбачають виконання курсового проекту «Розрахунок та проектування окремого фундаменту будівлі на природній ґрун- товій основі» як із викладачем, так і під час самостійної роботи. Можна використовувати також у підготовці курсового та дипломного про- ектування

Numerical simulation of blood flow and pressure drop in the pulmonary arterial and venous circulation

A novel multiscale mathematical and computational model of the pulmonary circulation is presented and used to analyse both arterial and venous pressure and flow. This work is a major advance over previous studies by Olufsen et al. (Ann Biomed Eng 28:1281–1299, 2012) which only considered the arterial circulation. For the first three generations of vessels within the pulmonary circulation, geometry is specified from patient-specific measurements obtained using magnetic resonance imaging (MRI). Blood flow and pressure in the larger arteries and veins are predicted using a nonlinear, cross-sectional-area-averaged system of equations for a Newtonian fluid in an elastic tube. Inflow into the main pulmonary artery is obtained from MRI measurements, while pressure entering the left atrium from the main pulmonary vein is kept constant at the normal mean value of 2 mmHg. Each terminal vessel in the network of ‘large’ arteries is connected to its corresponding terminal vein via a network of vessels representing the vascular bed of smaller arteries and veins. We develop and implement an algorithm to calculate the admittance of each vascular bed, using bifurcating structured trees and recursion. The structured-tree models take into account the geometry and material properties of the ‘smaller’ arteries and veins of radii ≥ 50 μ m. We study the effects on flow and pressure associated with three classes of pulmonary hypertension expressed via stiffening of larger and smaller vessels, and vascular rarefaction. The results of simulating these pathological conditions are in agreement with clinical observations, showing that the model has potential for assisting with diagnosis and treatment for circulatory diseases within the lung

Astrocyte pathology in the prefrontal cortex impairs the cognitive function of rats

Interest in astroglial cells is rising due to recent findings supporting dynamic neuron-astrocyte interactions. There is increasing evidence of astrocytic dysfunction in several brain disorders such as depression, schizophrenia or bipolar disorder; importantly these pathologies are characterized by the involvement of the prefrontal cortex and by significant cognitive impairments. Here, to model astrocyte pathology, we injected animals with the astrocyte specific toxin L-a-aminoadipate (L-AA) in the medial prefrontal cortex (mPFC); a behavioral and structural characterization two and six days after the injection was performed. Behavioral data shows that the astrocyte pathology in the mPFC affects the attentional set-shifting, the working memory and the reversal learning functions. Histological analysis of brain sections of the L-AA-injected animals revealed a pronounced loss of astrocytes in the targeted region. Interestingly, analysis of neurons in the lesion sites showed a progressive neuronal loss that was accompanied with dendritic atrophy in the surviving neurons. These results suggest that the L-AA-induced astrocytic loss in the mPFC triggers subsequent neuronal damage leading to cognitive impairment in tasks depending on the integrity of this brain region. These findings are of relevance to better understand the pathophysiological mechanisms underlying disorders that involve astrocytic loss/dysfunction in the PFC.This work was supported by the Marie Curie Fellowship FP7-PEOPLE-2010-IEF 273936, BIAL Foundation Grants 138/2008 and 61/2010, FEDER funds through Operational program for competitiveness factors-COMPETE -, ON2 Programa Operacional Regional do Norte (ON.2-O Novo Norte), QREN/FEDER, and by national funds through FCT-Foundation for Science and Technology-project (PTDC/SAU-NSC/118194/2010) and fellowships (SFRH/BPD/66151/2009 and SFRH/BD/89714/2012)

Impact of Dendritic Size and Dendritic Topology on Burst Firing in Pyramidal Cells

Neurons display a wide range of intrinsic firing patterns. A particularly relevant pattern for neuronal signaling and synaptic plasticity is burst firing, the generation of clusters of action potentials with short interspike intervals. Besides ion-channel composition, dendritic morphology appears to be an important factor modulating firing pattern. However, the underlying mechanisms are poorly understood, and the impact of morphology on burst firing remains insufficiently known. Dendritic morphology is not fixed but can undergo significant changes in many pathological conditions. Using computational models of neocortical pyramidal cells, we here show that not only the total length of the apical dendrite but also the topological structure of its branching pattern markedly influences inter- and intraburst spike intervals and even determines whether or not a cell exhibits burst firing. We found that there is only a range of dendritic sizes that supports burst firing, and that this range is modulated by dendritic topology. Either reducing or enlarging the dendritic tree, or merely modifying its topological structure without changing total dendritic length, can transform a cell's firing pattern from bursting to tonic firing. Interestingly, the results are largely independent of whether the cells are stimulated by current injection at the soma or by synapses distributed over the dendritic tree. By means of a novel measure called mean electrotonic path length, we show that the influence of dendritic morphology on burst firing is attributable to the effect both dendritic size and dendritic topology have, not on somatic input conductance, but on the average spatial extent of the dendritic tree and the spatiotemporal dynamics of the dendritic membrane potential. Our results suggest that alterations in size or topology of pyramidal cell morphology, such as observed in Alzheimer's disease, mental retardation, epilepsy, and chronic stress, could change neuronal burst firing and thus ultimately affect information processing and cognition

Deep sequencing analysis of the developing mouse brain reveals a novel microRNA

Extent: 15p.Background: MicroRNAs (miRNAs) are small non-coding RNAs that can exert multilevel inhibition/repression at a post-transcriptional or protein synthesis level during disease or development. Characterisation of miRNAs in adult mammalian brains by deep sequencing has been reported previously. However, to date, no small RNA profiling of the developing brain has been undertaken using this method. We have performed deep sequencing and small RNA analysis of a developing (E15.5) mouse brain. Results: We identified the expression of 294 known miRNAs in the E15.5 developing mouse brain, which were mostly represented by let-7 family and other brain-specific miRNAs such as miR-9 and miR-124. We also discovered 4 putative 22-23 nt miRNAs: mm_br_e15_1181, mm_br_e15_279920, mm_br_e15_96719 and mm_br_e15_294354 each with a 70-76 nt predicted pre-miRNA. We validated the 4 putative miRNAs and further characterised one of them, mm_br_e15_1181, throughout embryogenesis. Mm_br_e15_1181 biogenesis was Dicer1-dependent and was expressed in E3.5 blastocysts and E7 whole embryos. Embryo-wide expression patterns were observed at E9.5 and E11.5 followed by a near complete loss of expression by E13.5, with expression restricted to a specialised layer of cells within the developing and early postnatal brain. Mm_br_e15_1181 was upregulated during neurodifferentiation of P19 teratocarcinoma cells. This novel miRNA has been identified as miR-3099. Conclusions: We have generated and analysed the first deep sequencing dataset of small RNA sequences of the developing mouse brain. The analysis revealed a novel miRNA, miR-3099, with potential regulatory effects on early embryogenesis, and involvement in neuronal cell differentiation/function in the brain during late embryonic and early neonatal development.King-Hwa Ling, Peter J Brautigan, Christopher N Hahn, Tasman Daish, John R Rayner, Pike-See Cheah, Joy M Raison, Sandra Piltz Jeffrey R Mann, Deidre M Mattiske, Paul Q Thomas, David L Adelson and Hamish S Scot

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates