Development of an AAV-based model of tauopathy targeting retinal ganglion cells and the mouse visual pathway to study the role of microglia in Tau pathology.

Tauopathy is a typical feature of Alzheimer's disease of major importance because it strongly correlates with the severity of cognitive deficits experienced by patients. During the pathology, it follows a characteristic spatiotemporal course which takes its origin in the transentorhinal cortex, and then gradually invades the entire forebrain. To study the mechanisms of tauopathy, and test new therapeutic strategies, it is necessary to set-up relevant and versatile in vivo models allowing to recapitulate tauopathy. With this in mind, we have developed a model of tauopathy by overexpression of the human wild-type Tau protein in retinal ganglion cells in mice (RGCs). This overexpression led to the presence of hyperphosphorylated forms of the protein in the transduced cells as well as to their progressive degeneration. The application of this model to mice deficient in TREM2 (Triggering Receptor Expressed on Myeloid cells-2, an important genetic risk factor for AD) as well as to 15-month-old mice showed that microglia actively participate in the degeneration of RGCs. Surprisingly, although we were able to detect the transgenic Tau protein up to the terminal arborization of RGCs at the level of the superior colliculi, spreading of the transgenic Tau protein to post-synaptic neurons was detected only in aged animals. This suggests that there may be neuron-intrinsic- or microenvironment mediators facilitating this spreading that appear with aging.

Functional and neuropathological changes induced by injection of distinct alpha-synuclein strains: A pilot study in non-human primates.

The role of alpha-synuclein in Parkinson's disease has been heavily investigated since its discovery as a component of Lewy bodies. Recent rodent data demonstrate that alpha-synuclein strain structure is critical for differential propagation and toxicity. Based on these findings, we have compared, for the first time, in this pilot study, the capacity of two alpha-synuclein strains and patient-derived Lewy body extracts to model synucleinopathies after intra-putaminal injection in the non-human primate brain. Functional alterations triggered by these injections were evaluated in vivo using glucose positron emission tomography imaging. Post-mortem immunohistochemical and biochemical analyses were used to detect neuropathological alterations in the dopaminergic system and alpha-synuclein pathology propagation. In vivo results revealed a decrease in glucose metabolism more pronounced in alpha-synuclein strain-injected animals. Histology showed a decreased number of dopaminergic tyrosine hydroxylase-positive cells in the substantia nigra to different extents according to the inoculum used. Biochemistry revealed that alpha-synuclein-induced aggregation, phosphorylation, and propagation in different brain regions are strain-specific. Our findings show that distinct alpha-synuclein strains can induce specific patterns of synucleinopathy in the non-human primate, changes in the nigrostriatal pathway, and functional alterations that resemble early-stage Parkinson's disease.

giRAff: an automated atlas segmentation tool adapted to single histological slices.

Conventional histology of the brain remains the gold standard in the analysis of animal models. In most biological studies, standard protocols usually involve producing a limited number of histological slices to be analyzed. These slices are often selected into a specific anatomical region of interest or around a specific pathological lesion. Due to the lack of automated solutions to analyze such single slices, neurobiologists perform the segmentation of anatomical regions manually most of the time. Because the task is long, tedious, and operator-dependent, we propose an automated atlas segmentation method called giRAff, which combines rigid and affine registrations and is suitable for conventional histological protocols involving any number of single slices from a given mouse brain. In particular, the method has been tested on several routine experimental protocols involving different anatomical regions of different sizes and for several brains. For a given set of single slices, the method can automatically identify the corresponding slices in the mouse Allen atlas template with good accuracy and segmentations comparable to those of an expert. This versatile and generic method allows the segmentation of any single slice without additional anatomical context in about 1 min. Basically, our proposed giRAff method is an easy-to-use, rapid, and automated atlas segmentation tool compliant with a wide variety of standard histological protocols.

A general deep learning framework for neuron instance segmentation based on Efficient UNet and morphological post-processing.

Recent studies have demonstrated the superiority of deep learning in medical image analysis, especially in cell instance segmentation, a fundamental step for many biological studies. However, the excellent performance of the neural networks requires training on large, unbiased dataset and annotations, which is labor-intensive and expertise-demanding. This paper presents an end-to-end framework to automatically detect and segment NeuN stained neuronal cells on histological images using only point annotations. Unlike traditional nuclei segmentation with point annotation, we propose using point annotation and binary segmentation to synthesize pixel-level annotations. The synthetic masks are used as the ground truth to train the neural network, a U-Net-like architecture with a state-of-the-art network, EfficientNet, as the encoder. Validation results show the superiority of our model compared to other recent methods. In addition, we investigated multiple post-processing schemes and proposed an original strategy to convert the probability map into segmented instances using ultimate erosion and dynamic reconstruction. This approach is easy to configure and outperforms other classical post-processing techniques. This work aims to develop a robust and efficient framework for analyzing neurons using optical microscopic data, which can be used in preclinical biological studies and, more specifically, in the context of neurodegenerative diseases. Code is available at: https://github.com/MIRCen/NeuronInstanceSeg.

Automated Atlas-based Segmentation of Single Coronal Mouse Brain Slices using Linear 2D-2D Registration.

A significant challenge for brain histological data analysis is to precisely identify anatomical regions in order to perform accurate local quantifications and evaluate therapeutic solutions. Usually, this task is performed manually, becoming therefore tedious and subjective. Another option is to use automatic or semi-automatic methods, among which segmentation using digital atlases co-registration. However, most available atlases are 3D, whereas digitized histological data are 2D. Methods to perform such 2D-3D segmentation from an atlas are required. This paper proposes a strategy to automatically and accurately segment single 2D coronal slices within a 3D volume of atlas, using linear registration. We validated its robustness and performance using an exploratory approach at whole-brain scale.

Evaluation of Deep Learning Topcoders Method for Neuron Individualization in Histological Macaque Brain Section.

Cell individualization has a vital role in digital pathology image analysis. Deep Learning is considered as an efficient tool for instance segmentation tasks, including cell individualization. However, the precision of the Deep Learning model relies on massive unbiased dataset and manual pixel-level annotations, which is labor intensive. Moreover, most applications of Deep Learning have been developed for processing oncological data. To overcome these challenges, i) we established a pipeline to synthesize pixel-level labels with only point annotations provided; ii) we tested an ensemble Deep Learning algorithm to perform cell individualization on neurological data. Results suggest that the proposed method successfully segments neuronal cells in both object-level and pixel-level, with an average detection accuracy of 0.93.

The C-Terminal Domain of LRRK2 with the G2019S Substitution Increases Mutant A53T α-Synuclein Toxicity in Dopaminergic Neurons In Vivo.

Alpha-synuclein (α-syn) and leucine-rich repeat kinase 2 (LRRK2) play crucial roles in Parkinson's disease (PD). They may functionally interact to induce the degeneration of dopaminergic (DA) neurons via mechanisms that are not yet fully understood. We previously showed that the C-terminal portion of LRRK2 (ΔLRRK2) with the G2019S mutation (ΔLRRK2G2019S) was sufficient to induce neurodegeneration of DA neurons in vivo, suggesting that mutated LRRK2 induces neurotoxicity through mechanisms that are (i) independent of the N-terminal domains and (ii) "cell-autonomous". Here, we explored whether ΔLRRK2G2019S could modify α-syn toxicity through these two mechanisms. We used a co-transduction approach in rats with AAV vectors encoding ΔLRRK2G2019S or its "dead" kinase form, ΔLRRK2DK, and human α-syn with the A53T mutation (AAV-α-synA53T). Behavioral and histological evaluations were performed at 6- and 15-weeks post-injection. Results showed that neither form of ΔLRRK2 alone induced the degeneration of neurons at these post-injection time points. By contrast, injection of AAV-α-synA53T alone resulted in motor signs and degeneration of DA neurons. Co-injection of AAV-α-synA53T with AAV-ΔLRRK2G2019S induced DA neuron degeneration that was significantly higher than that induced by AAV-α-synA53T alone or with AAV-ΔLRRK2DK. Thus, mutated α-syn neurotoxicity can be enhanced by the C-terminal domain of LRRK2G2019 alone, through cell-autonomous mechanisms.

THY-Tau22 mouse model accumulates more tauopathy at late stage of the disease in response to microglia deactivation through TREM2 deficiency.

The role played by microglia has taken the center of the stage in the etiology of Alzheimer's disease (AD). Several genome-wide association studies carried out on large cohorts of patients have indeed revealed a large number of genetic susceptibility factors corresponding to genes involved in neuroinflammation and expressed specifically by microglia in the brain. Among these genes TREM2, a cell surface receptor expressed by microglia, arouses strong interest because its R47H variant confers a risk of developing AD comparable to the ε4 allele of the APOE gene. Since this discovery, a growing number of studies have therefore examined the role played by TREM2 in the evolution of amyloid plaques and neurofibrillary tangles, the two brain lesions characteristic of AD. Many studies report conflicting results, reflecting the complex nature of microglial activation in AD. Here, we investigated the impact of TREM2 deficiency in the THY-Tau22 transgenic line, a well-characterized model of tauopathy. Our study reports an increase in the severity of tauopathy lesions in mice deficient in TREM2 occurring at an advanced stage of the pathology. This exacerbation of pathology was associated with a reduction in microglial activation indicated by typical morphological features and altered expression of specific markers. However, it was not accompanied by any further changes in memory performance. Our longitudinal study confirms that a defect in microglial TREM2 signaling leads to an increase in neuronal tauopathy occurring only at late stages of the disease.

Complete spatial characterisation of N-glycosylation upon striatal neuroinflammation in the rodent brain.

BACKGROUND: Neuroinflammation is an underlying pathology of all neurological conditions, the understanding of which is still being comprehended. A specific molecular pathway that has been overlooked in neuroinflammation is glycosylation (i.e., post-translational addition of glycans to the protein structure). N-glycosylation is a specific type of glycosylation with a cardinal role in the central nervous system (CNS), which is highlighted by congenital glycosylation diseases that result in neuropathological symptoms such as epilepsy and mental retardation. Changes in N-glycosylation can ultimately affect glycoproteins' functions, which will have an impact on cell machinery. Therefore, characterisation of N-glycosylation alterations in a neuroinflammatory scenario can provide a potential target for future therapies. METHODS: With that aim, the unilateral intrastriatal injection of lipopolysaccharide (LPS) in the adult rat brain was used as a model of neuroinflammation. In vivo and post-mortem, quantitative and spatial characterisation of both neuroinflammation and N-glycome was performed at 1-week post-injection of LPS. These aspects were investigated through a multifaceted approach based on positron emission tomography (PET), quantitative histology, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), liquid chromatography and matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI). RESULTS: In the brain region showing LPS-induced neuroinflammation, a significant decrease in the abundance of sialylated and core fucosylated structures was seen (approximately 7.5% and 8.5%, respectively), whereas oligomannose N-glycans were significantly increased (13.5%). This was confirmed by MALDI-MSI, which provided a high-resolution spatial distribution of N-glycans, allowing precise comparison between normal and diseased brain hemispheres. CONCLUSIONS: Together, our data show for the first time the complete profiling of N-glycomic changes in a well-characterised animal model of neuroinflammation. These data represent a pioneering step to identify critical targets that may modulate neuroinflammation in neurodegenerative diseases.

Neuronal tau species transfer to astrocytes and induce their loss according to tau aggregation state.

Deposits of different abnormal forms of tau in neurons and astrocytes represent key anatomo-pathological features of tauopathies. Although tau protein is highly enriched in neurons and poorly expressed by astrocytes, the origin of astrocytic tau is still elusive. Here, we used innovative gene transfer tools to model tauopathies in adult mouse brains and to investigate the origin of astrocytic tau. We showed in our adeno-associated virus (AAV)-based models and in Thy-Tau22 transgenic mice that astrocytic tau pathology can emerge secondarily to neuronal pathology. By designing an in vivo reporter system, we further demonstrated bidirectional exchanges of tau species between neurons and astrocytes. We then determined the consequences of tau accumulation in astrocytes on their survival in models displaying various status of tau aggregation. Using stereological counting of astrocytes, we report that, as for neurons, soluble tau species are highly toxic to some subpopulations of astrocytes in the hippocampus, whereas the accumulation of tau aggregates does not affect their survival. Thus, astrocytes are not mere bystanders of neuronal pathology. Our results strongly suggest that tau pathology in astrocytes may significantly contribute to clinical symptoms.

Evaluation of automated segmentation algorithms for neurons in macaque cerebral microscopic images.

Accurate cerebral neuron segmentation is required before neuron counting and neuron morphological analysis. Numerous algorithms for neuron segmentation have been published, but they are mainly evaluated using limited subsets from a specific anatomical region, targeting neurons of clear contrast and/or neurons with similar staining intensity. It is thus unclear how these algorithms perform on cerebral neurons in diverse anatomical regions. In this article, we introduce and reliably evaluate existing machine learning algorithms using a data set of microscopy images of macaque brain. This data set highlights various anatomical regions (e.g., cortex, caudate, thalamus, claustrum, putamen, hippocampus, subiculum, lateral geniculate, globus pallidus, etc.), poor contrast, and staining intensity differences of neurons. The evaluation was performed using 10 architectures of six classic machine learning algorithms in terms of typical Recall, Precision, F-score, aggregated Jaccard index (AJI), as well as a performance ranking of algorithms. F-score of most of the algorithms is superior to 0.7. Deep learning algorithms facilitate generally higher F-scores. U-net with suitable layer depth has been evaluated to be excellent classifiers with F-score of 0.846 and 0.837 when performing cross validation. The evaluation and analysis indicate the performance gap among algorithms in various anatomical regions and the strengths and limitations of each algorithm. The comparative result highlights at the same time the importance and difficulty of neuron segmentation and provides clues for future improvement. To the best of our knowledge, this work is the first comprehensive study for neuron segmentation in such large-scale anatomical regions. Neuron segmentation plays a critical role in extracting cerebral information, such as neuron counting and neuron morphological analysis. Accurate automated cerebral neuron segmentation is a challenging task due to different kinds, poor contrast, staining intensity differences, and fuzzy boundaries of neurons. The comprehensive evaluation and analysis of performance among existing machine learning algorithms in diverse anatomical regions allows to make clear of the strengths and limitations of state-of-the-art algorithm. The comprehensive study provides clues for future improvement and creation of automated methods.

Assessment of simplified methods for quantification of [18F]-DPA-714 using 3D whole-brain TSPO immunohistochemistry in a non-human primate.

The 18 kDa translocator protein (TSPO) is the main molecular target to image neuroinflammation by positron emission tomography (PET). However, TSPO-PET quantification is complex and none of the kinetic modelling approaches has been validated using a voxel-by-voxel comparison of TSPO-PET data with the actual TSPO levels of expression. Here, we present a single case study of binary classification of in vivo PET data to evaluate the statistical performance of different TSPO-PET quantification methods. To that end, we induced a localized and adjustable increase of TSPO levels in a non-human primate brain through a viral-vector strategy. We then performed a voxel-wise comparison of the different TSPO-PET quantification approaches providing parametric [18F]-DPA-714 PET images, with co-registered in vitro three-dimensional TSPO immunohistochemistry (3D-IHC) data. A data matrix was extracted from each brain hemisphere, containing the TSPO-IHC and TSPO-PET data for each voxel position. Each voxel was then classified as false or true, positive or negative after comparison of the TSPO-PET measure to the reference 3D-IHC method. Finally, receiver operating characteristic curves (ROC) were calculated for each TSPO-PET quantification method. Our results show that standard uptake value ratios using cerebellum as a reference region (SUVCBL) has the most optimal ROC score amongst all non-invasive approaches.

The C-terminal domain of LRRK2 with the G2019S mutation is sufficient to produce neurodegeneration of dopaminergic neurons in vivo.

The G2019S substitution in the kinase domain of LRRK2 (LRRK2G2019S) is the most prevalent mutation associated with Parkinson's disease (PD). Neurotoxic effects of LRRK2G2019S are thought to result from an increase in its kinase activity as compared to wild type LRRK2. However, it is unclear whether the kinase domain of LRRK2G2019S is sufficient to trigger degeneration or if the full length protein is required. To address this question, we generated constructs corresponding to the C-terminal domain of LRRK2 (ΔLRRK2). A kinase activity that was increased by G2019➔S substitution could be detected in ΔLRRK2. However biochemical experiments suggested it did not bind or phosphorylate the substrate RAB10, in contrast to full length LRRK2. The overexpression of ΔLRRK2G2019S in the rat striatum using lentiviral vectors (LVs) offered a straightforward and simple way to investigate its effects in neurons in vivo. Results from a RT-qPCR array analysis indicated that ΔLRRK2G2019S led to significant mRNA expression changes consistent with a kinase-dependent mechanism. We next asked whether ΔLRRK2 could be sufficient to trigger neurodegeneration in the substantia nigra pars compacta (SNc) in adult rats. Six months after infection of the substantia nigra pars compacta (SNc) with LV-ΔLRRK2WT or LV-ΔLRRK2G2019S, the number of DA neurons was unchanged. To examine whether higher levels of ΔLRRK2G2019S could trigger degeneration we cloned ΔLRRK2 in AAV2/9 construct. As expected, AAV2/9 injected in the SNc led to neuronal expression of ΔLRRK2WT and ΔLRRK2G2019S at much higher levels than those obtained with LVs. Six months after injection, unbiased stereology showed that AAV-ΔLRRK2G2019S produced a significant ~30% loss of neurons positive for tyrosine hydroxylase- and for the vesicular dopamine transporter whereas AAV-ΔLRRK2WT did not. These findings show that overexpression of the C-terminal part of LRRK2 containing the mutant kinase domain is sufficient to trigger degeneration of DA neurons, through cell-autonomous mechanisms, possibly independent of RAB10.

MHC matching fails to prevent long-term rejection of iPSC-derived neurons in non-human primates.

Cell therapy products (CTP) derived from pluripotent stem cells (iPSCs) may constitute a renewable, specifically differentiated source of cells to potentially cure patients with neurodegenerative disorders. However, the immunogenicity of CTP remains a major issue for therapeutic approaches based on transplantation of non-autologous stem cell-derived neural grafts. Despite its considerable side-effects, long-term immunosuppression, appears indispensable to mitigate neuro-inflammation and prevent rejection of allogeneic CTP. Matching iPSC donors' and patients' HLA haplotypes has been proposed as a way to access CTP with enhanced immunological compatibility, ultimately reducing the need for immunosuppression. In the present work, we challenge this paradigm by grafting autologous, MHC-matched and mis-matched neuronal grafts in a primate model of Huntington's disease. Unlike previous reports in unlesioned hosts, we show that in the absence of immunosuppression MHC matching alone is insufficient to grant long-term survival of neuronal grafts in the lesioned brain.

Gene Therapy for Parkinson's Disease: Preclinical Evaluation of Optimally Configured TH:CH1 Fusion for Maximal Dopamine Synthesis.

A recent phase I-II, open-label trial of ProSavin, a lentiviral vector delivering the key enzymes in the dopamine biosynthetic pathway to non-dopaminergic striatal neurons, demonstrated safety and improved motor function in parkinsonian patients. However, the magnitude of the effect suggested that optimal levels of dopamine replacement may not have been achieved. OXB-102, a lentiviral vector with an optimized expression cassette for dopamine biosynthesis, has been shown to achieve a significantly higher dopamine yield than ProSavin. We assessed the efficacy of OXB-102 in the MPTP macaque model of Parkinson's disease (PD). At 6 months post-vector administration, all treated animals showed significant improvements in clinical scores and spontaneous locomotor activity compared to controls, with the highest recovery observed in the OXB-102 high-dose (HD) group. Positron emission tomography quantification of 6-[18F]-fluoro-L-m-tyrosine uptake showed a significant increase in amino acid decarboxylase activity for all treated animals, compared with controls, where the OXB-102 HD group showed the highest level of dopaminergic activity. A toxicology study in macaques demonstrated that the vector was safe and well tolerated, with no associated clinical or behavioral abnormalities and no immune response mounted against any transgene products. Overall, these data support the further clinical development of OXB-102 for the treatment of PD.

Tridimensional mapping of Phox2b expressing neurons in the brainstem of adult Macaca fascicularis and identification of the retrotrapezoid nucleus.

Chemosensitivity is a key mechanism for the regulation of breathing in vertebrates. The retrotrapezoid nucleus is a crucial hub for respiratory chemoreception within the brainstem. It integrates chemosensory information that are both peripheral from the carotid bodies (via the nucleus of the solitary tract) and central through the direct sensing of extracellular protons. To date, the location of a genetically defined RTN has only been ascertained in rodents. We first demonstrated that Phox2b, a key determinant for the development of the visceral nervous system and branchiomotor nuclei in the brainstem including the RTN, had a similar distribution in the brainstem of adult macaques compared to adult rats. Second, based on previous description of a specific molecular signature for the RTN in rats, and on an innovative technique for duplex in situ hybridization, we identified parafacial neurons which coexpressed Phox2b and ppGal mRNAs. They were located ventrally to the nucleus of the facial nerve and extended from the caudal part of the nucleus of the superior olive to the rostral tip of the inferior olive. Using the previously described blockface technique, deformations were corrected to allow the proper alignment and stacking of digitized sections, hence providing for the first time a 3D reconstruction of the macaque brainstem, Phox2b distribution and the primate retrotrapezoid nucleus. This description should help bridging the gap between rodents and humans for the description of key respiratory structures in the brainstem.

Longitudinal characterization of cognitive and motor deficits in an excitotoxic lesion model of striatal dysfunction in non-human primates.

As research progresses in the understanding of the molecular and cellular mechanisms underlying neurodegenerative diseases like Huntington's disease (HD) and expands towards preclinical work for the development of new therapies, highly relevant animal models are increasingly needed to test new hypotheses and to validate new therapeutic approaches. In this light, we characterized an excitotoxic lesion model of striatal dysfunction in non-human primates (NHPs) using cognitive and motor behaviour assessment as well as functional imaging and post-mortem anatomical analyses. NHPs received intra-striatal stereotaxic injections of quinolinic acid bilaterally in the caudate nucleus and unilaterally in the left sensorimotor putamen. Post-operative MRI scans showed atrophy of the caudate nucleus and a large ventricular enlargement in all 6 NHPs that correlated with post-mortem measurements. Behavioral analysis showed deficits in 2 analogues of the Wisconsin card sorting test (perseverative behavior) and in an executive task, while no deficits were observed in a visual recognition or an episodic memory task at 6 months following surgery. Spontaneous locomotor activity was decreased after lesion and the incidence of apomorphine-induced dyskinesias was significantly increased at 3 and 6 months following lesion. Positron emission tomography scans obtained at end-point showed a major deficit in glucose metabolism and D2 receptor density limited to the lesioned striatum of all NHPs compared to controls. Post-mortem analyses revealed a significant loss of medium-sized spiny neurons in the striatum, a loss of neurons and fibers in the globus pallidus, a unilateral decrease in dopaminergic neurons of the substantia nigra and a loss of neurons in the motor and dorsolateral prefrontal cortex. Overall, we show that this robust NHP model presents specific behavioral (learning, execution and retention of cognitive tests) and metabolic functional deficits that, to the best of our knowledge, are currently not mimicked in any available large animal model of striatal dysfunction. Moreover, we used non-invasive, translational techniques like behavior and imaging to quantify such deficits and found that they correlate to a significant cell loss in the striatum and its main input and output structures. This model can thus significantly contribute to the pre-clinical longitudinal evaluation of the ability of new therapeutic cell, gene or pharmacotherapy approaches in restoring the functionality of the striatal circuitry.

Automated Individualization of Size-Varying and Touching Neurons in Macaque Cerebral Microscopic Images.

In biomedical research, cell analysis is important to assess physiological and pathophysiological information. Virtual microscopy offers the unique possibility to study the compositions of tissues at a cellular scale. However, images acquired at such high spatial resolution are massive, contain complex information, and are therefore difficult to analyze automatically. In this article, we address the problem of individualization of size-varying and touching neurons in optical microscopy two-dimensional (2-D) images. Our approach is based on a series of processing steps that incorporate increasingly more information. (1) After a step of segmentation of neuron class using a Random Forest classifier, a novel min-max filter is used to enhance neurons' centroids and boundaries, enabling the use of region growing process based on a contour-based model to drive it to neuron boundary and achieve individualization of touching neurons. (2) Taking into account size-varying neurons, an adaptive multiscale procedure aiming at individualizing touching neurons is proposed. This protocol was evaluated in 17 major anatomical regions from three NeuN-stained macaque brain sections presenting diverse and comprehensive neuron densities. Qualitative and quantitative analyses demonstrate that the proposed method provides satisfactory results in most regions (e.g., caudate, cortex, subiculum, and putamen) and outperforms a baseline Watershed algorithm. Neuron counts obtained with our method show high correlation with an adapted stereology technique performed by two experts (respectively, 0.983 and 0.975 for the two experts). Neuron diameters obtained with our method ranged between 2 and 28.6 µm, matching values reported in the literature. Further works will aim to evaluate the impact of staining and interindividual variability on our protocol.

The striatal kinase DCLK3 produces neuroprotection against mutant huntingtin.

The neurobiological functions of a number of kinases expressed in the brain are unknown. Here, we report new findings on DCLK3 (doublecortin like kinase 3), which is preferentially expressed in neurons in the striatum and dentate gyrus. Its function has never been investigated. DCLK3 expression is markedly reduced in Huntington's disease. Recent data obtained in studies related to cancer suggest DCLK3 could have an anti-apoptotic effect. Thus, we hypothesized that early loss of DCLK3 in Huntington's disease may render striatal neurons more susceptible to mutant huntingtin (mHtt). We discovered that DCLK3 silencing in the striatum of mice exacerbated the toxicity of an N-terminal fragment of mHtt. Conversely, overexpression of DCLK3 reduced neurodegeneration produced by mHtt. DCLK3 also produced beneficial effects on motor symptoms in a knock-in mouse model of Huntington's disease. Using different mutants of DCLK3, we found that the kinase activity of the protein plays a key role in neuroprotection. To investigate the potential mechanisms underlying DCLK3 effects, we studied the transcriptional changes produced by the kinase domain in human striatal neurons in culture. Results show that DCLK3 regulates in a kinase-dependent manner the expression of many genes involved in transcription regulation and nucleosome/chromatin remodelling. Consistent with this, histological evaluation showed DCLK3 is present in the nucleus of striatal neurons and, protein-protein interaction experiments suggested that the kinase domain interacts with zinc finger proteins, including the transcriptional activator adaptor TADA3, a core component of the Spt-ada-Gcn5 acetyltransferase (SAGA) complex which links histone acetylation to the transcription machinery. Our novel findings suggest that the presence of DCLK3 in striatal neurons may play a key role in transcription regulation and chromatin remodelling in these brain cells, and show that reduced expression of the kinase in Huntington's disease could render the striatum highly vulnerable to neurodegeneration.

Three-dimensional SPACE fluid-attenuated inversion recovery at 3 T to improve subthalamic nucleus lead placement for deep brain stimulation in Parkinson's disease: from preclinical to clinical studies.

OBJECTIVE Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-established therapy for motor symptoms in patients with pharmacoresistant Parkinson's disease (PD). However, the procedure, which requires multimodal perioperative exploration such as imaging, electrophysiology, or clinical examination during macrostimulation to secure lead positioning, remains challenging because the STN cannot be reliably visualized using the gold standard, T2-weighted imaging (T2WI) at 1.5 T. Thus, there is a need to improve imaging tools to better visualize the STN, optimize DBS lead implantation, and enlarge DBS diffusion. METHODS Gradient-echo sequences such as those used in T2WI suffer from higher distortions at higher magnetic fields than spin-echo sequences. First, a spin-echo 3D SPACE (sampling perfection with application-optimized contrasts using different flip angle evolutions) FLAIR sequence at 3 T was designed, validated histologically in 2 nonhuman primates, and applied to 10 patients with PD; their data were clinically compared in a double-blind manner with those of a control group of 10 other patients with PD in whom STN targeting was performed using T2WI. RESULTS Overlap between the nonhuman primate STNs segmented on 3D-histological and on 3D-SPACE-FLAIR volumes was high for the 3 most anterior quarters (mean [± SD] Dice scores 0.73 ± 0.11, 0.74 ± 0.06, and 0.60 ± 0.09). STN limits determined by the 3D-SPACE-FLAIR sequence were more consistent with electrophysiological edges than those determined by T2WI (0.9 vs 1.4 mm, respectively). The imaging contrast of the STN on the 3D-SPACE-FLAIR sequence was 4 times higher (p < 0.05). Improvement in the Unified Parkinson's Disease Rating Scale Part III score (off medication, on stimulation) 12 months after the operation was higher for patients who underwent 3D-SPACE-FLAIR-guided implantation than for those in whom T2WI was used (62.2% vs 43.6%, respectively; p < 0.05). The total electrical energy delivered decreased by 36.3% with the 3D-SPACE-FLAIR sequence (p < 0.05). CONCLUSIONS 3D-SPACE-FLAIR sequences at 3 T improved STN lead placement under stereotactic conditions, improved the clinical outcome of patients with PD, and increased the benefit/risk ratio of STN-DBS surgery.