Improving tremor response to focused ultrasound thalamotomy

MRI-guided high-intensity focused ultrasound thalamotomy is an incisionless therapy for essential tremor. To reduce adverse effects, the field has migrated to treating at 2 mm above the anterior commissure-posterior commissure plane. We perform MRI-guided high-intensity focused ultrasound with an advanced imaging targeting technique, four-tract tractography. Four-tract tractography uses diffusion tensor imaging to identify the critical white matter targets for tremor control, the decussating and non-decussating dentatorubrothalamic tracts, while the corticospinal tract and medial lemniscus are identified to be avoided. In some patients, four-tract tractography identified a risk of damaging the medial lemniscus or corticospinal tract if treated at 2 mm superior to the anterior commissure-posterior commissure plane. In these patients, we chose to target 1.2-1.5 mm superior to the anterior commissure-posterior commissure plane. In these patients, post-operative imaging revealed that the focused ultrasound lesion extended into the posterior subthalamic area. This study sought to determine if patients with focused ultrasound lesions that extend into the posterior subthalamic area have a differnce in tremor improvement than those without. Twenty essential tremor patients underwent MRI-guided high-intensity focused ultrasound and were retrospectively classified into two groups. Group 1 included patients with an extension of the thalamic-focused ultrasound lesion into the posterior subthalamic area. Group 2 included patients without extension of the thalamic-focused ultrasound lesion into the posterior subthalamic area. For each patient, the percent change in postural tremor, kinetic tremor and Archimedes spiral scores were calculated between baseline and a 3-month follow-up. Two-tailed Wilcoxon rank-sum tests were used to compare the improvement in tremor scores, the total number of sonications, thermal dose to achieve initial tremor response, and skull density ratio between groups. Group 1 had significantly greater postural, kinetic, and Archimedes spiral score percent improvement than Group 2 (P values: 5.41 × 10-5, 4.87 × 10-4, and 5.41 × 10-5, respectively). Group 1 also required significantly fewer total sonications to control the tremor and a significantly lower thermal dose to achieve tremor response (P values: 6.60 × 10-4 and 1.08 × 10-5, respectively). No significant group differences in skull density ratio were observed (P = 1.0). We do not advocate directly targeting the posterior subthalamic area with MRI-guided high-intensity focused ultrasound because the shape of the focused ultrasound lesion can result in a high risk of adverse effects. However, when focused ultrasound lesions naturally extend from the thalamus into the posterior subthalamic area, they provide greater tremor control than those that only involve the thalamus.

Focused ultrasound using a novel targeting method four-tract tractography for magnetic resonance-guided high-intensity focused ultrasound targeting

Magnetic resonance-guided high-intensity focused ultrasound thalamotomy is a Food and Drug Administration-approved treatment for essential tremor. The target, the ventral intermediate nucleus of the thalamus, is not visualized on standard, anatomic MRI sequences. Several recent reports have used diffusion tensor imaging to target the dentato-rubro-thalamic-tract. There is considerable variability in fibre tracking algorithms and what fibres are tracked. Targeting discrete white matter tracts with magnetic resonance-guided high-intensity focused ultrasound is an emerging precision medicine technique that has the promise to improve patient outcomes and reduce treatment times. We provide a technical overview and clinical benefits of our novel, easily implemented advanced tractography method: four-tract tractography. Our method is novel because it targets both the decussating and non-decussating dentato-rubro-thalamic-tracts while avoiding the medial lemniscus and corticospinal tracts. Our method utilizes Food and Drug Administration-approved software and is easily implementable into existing workflows. Initial experience using this approach suggests that it improves patient outcomes by reducing the incidence of adverse effects.

Model-based and Model-free Machine Learning Techniques for Diagnostic Prediction and Classification of Clinical Outcomes in Parkinson's Disease

In this study, we apply a multidisciplinary approach to investigate falls in PD patients using clinical, demographic and neuroimaging data from two independent initiatives (University of Michigan and Tel Aviv Sourasky Medical Center). Using machine learning techniques, we construct predictive models to discriminate fallers and non-fallers. Through controlled feature selection, we identified the most salient predictors of patient falls including gait speed, Hoehn and Yahr stage, postural instability and gait difficulty-related measurements. The model-based and model-free analytical methods we employed included logistic regression, random forests, support vector machines, and XGboost. The reliability of the forecasts was assessed by internal statistical (5-fold) cross validation as well as by external out-of-bag validation. Four specific challenges were addressed in the study: Challenge 1, develop a protocol for harmonizing and aggregating complex, multisource, and multi-site Parkinson's disease data; Challenge 2, identify salient predictive features associated with specific clinical traits, e.g., patient falls; Challenge 3, forecast patient falls and evaluate the classification performance; and Challenge 4, predict tremor dominance (TD) vs. posture instability and gait difficulty (PIGD). Our findings suggest that, compared to other approaches, model-free machine learning based techniques provide a more reliable clinical outcome forecasting of falls in Parkinson's patients, for example, with a classification accuracy of about 70-80%.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

BACKGROUND

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data.

METHODS AND FINDINGS

Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting.

CONCLUSIONS

Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

Clinical and scientific perspectives on movement disorders: Stanley Fahn's contributions

Dr. Stanley Fahn, the H. Houston Merritt Professor of Neurology and Director Emeritus of the Center for Parkinson's Disease and Other Movement Disorders at Columbia University, one of the founders of the field of movement disorders, was the first president of the Movement Disorders Society (subsequently renamed as the International Parkinson and Movement Disorder Society). Together with his friend and colleague, Professor David Marsden, he also served as the first co-editor of the journal Movement Disorders. By emphasizing phenomenology as the key element in differentiating various hypokinetic and hyperkinetic movement disorders, Dr. Fahn drew attention to the clinical history and the power of observation in the diagnosis of movement disorders. Dr. Fahn had major influence on the development of classifications and assessments of various movement disorders and in organizing various research groups such as the Parkinson Study Group. As the founder and president of the World Parkinson Coalition and an organizer of the initial three World Parkinson Congresses, he has demonstrated his long-standing commitment to the cause of including patients as partners. The primary goal and objective of this invited review is to highlight some of Dr. Fahn's most impactful scientific and clinical contributions to the understanding and treatment of Parkinson's disease, dystonia, and other movement disorders.

Inherited isolated dystonia: clinical genetics and gene function

Isolated inherited dystonia-formerly referred to as primary dystonia-is characterized by abnormal motor functioning of a grossly normal appearing brain. The disease manifests as abnormal involuntary twisting movements. The absence of overt neuropathological lesions, while intriguing, has made it particularly difficult to unravel the pathogenesis of isolated inherited dystonia. The explosion of genetic techology enabling the identification of the causative gene mutations is transforming our understanding of dystonia pathogenesis, as the molecular, cellular and circuit level consequences of these mutations are identified in experimental systems. Here, I review the clinical genetics and cell biology of three forms of inherited dystonia for which the causative mutation is known: DYT1 (TOR1A), DYT6 (THAP1), DYT25 (GNAL).

Nuclear envelope breakdown induced by herpes simplex virus type 1 involves the activity of viral fusion proteins

Herpesvirus infection reorganizes components of the nuclear lamina usually without loss of integrity of the nuclear membranes. We report that wild-type HSV infection can cause dissolution of the nuclear envelope in transformed mouse embryonic fibroblasts that do not express torsinA. Nuclear envelope breakdown is accompanied by an eight-fold inhibition of virus replication. Breakdown of the membrane is much more limited during infection with viruses that lack the gB and gH genes, suggesting that breakdown involves factors that promote fusion at the nuclear membrane. Nuclear envelope breakdown is also inhibited during infection with virus that does not express UL34, but is enhanced when the US3 gene is deleted, suggesting that envelope breakdown may be enhanced by nuclear lamina disruption. Nuclear envelope breakdown cannot compensate for deletion of the UL34 gene suggesting that mixing of nuclear and cytoplasmic contents is insufficient to bypass loss of the normal nuclear egress pathway.

Interplay of LRRK2 with chaperone-mediated autophagy

Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common cause of familial Parkinson's disease. We found LRRK2 to be degraded in lysosomes by chaperone-mediated autophagy (CMA), whereas the most common pathogenic mutant form of LRRK2, G2019S, was poorly degraded by this pathway. In contrast to the behavior of typical CMA substrates, lysosomal binding of both wild-type and several pathogenic mutant LRRK2 proteins was enhanced in the presence of other CMA substrates, which interfered with the organization of the CMA translocation complex, resulting in defective CMA. Cells responded to such LRRK2-mediated CMA compromise by increasing levels of the CMA lysosomal receptor, as seen in neuronal cultures and brains of LRRK2 transgenic mice, induced pluripotent stem cell-derived dopaminergic neurons and brains of Parkinson's disease patients with LRRK2 mutations. This newly described LRRK2 self-perpetuating inhibitory effect on CMA could underlie toxicity in Parkinson's disease by compromising the degradation of α-synuclein, another Parkinson's disease-related protein degraded by this pathway.

Contextual automated 3D analysis of subcellular organelles adapted to high-content screening

Advances in automated imaging microscopy allow fast acquisitions of multidimensional biological samples. Those microscopes open new possibilities for analyzing subcellular structures and spatial cellular arrangements. In this article, the authors describe a 3D image analysis framework adapted to medium-throughput screening. Upon adaptive and regularized segmentation, followed by precise 3D reconstruction, they achieve automatic quantification of numerous relevant 3D descriptors related to the shape, texture, and fluorescence intensity of multiple stained subcellular structures. A global analysis of the 3D reconstructed scene shows additional possibilities to quantify the relative position of organelles. Implementing this methodology, the authors analyzed the subcellular reorganization of the nucleus, the Golgi apparatus, and the centrioles occurring during the cell cycle. In addition, they quantified the effect of a genetic mutation associated with the early onset primary dystonia on the redistribution of torsinA from the bulk endoplasmic reticulum to the perinuclear space of the nuclear envelope. They show that their method enables the classification of various translocation levels of torsinA and opens the possibility for compound-based screening campaigns restoring the normal torsinA phenotype.

Dopamine-modified alpha-synuclein blocks chaperone-mediated autophagy

Altered degradation of alpha-synuclein (alpha-syn) has been implicated in the pathogenesis of Parkinson disease (PD). We have shown that alpha-syn can be degraded via chaperone-mediated autophagy (CMA), a selective lysosomal mechanism for degradation of cytosolic proteins. Pathogenic mutants of alpha-syn block lysosomal translocation, impairing their own degradation along with that of other CMA substrates. While pathogenic alpha-syn mutations are rare, alpha-syn undergoes posttranslational modifications, which may underlie its accumulation in cytosolic aggregates in most forms of PD. Using mouse ventral medial neuron cultures, SH-SY5Y cells in culture, and isolated mouse lysosomes, we have found that most of these posttranslational modifications of alpha-syn impair degradation of this protein by CMA but do not affect degradation of other substrates. Dopamine-modified alpha-syn, however, is not only poorly degraded by CMA but also blocks degradation of other substrates by this pathway. As blockage of CMA increases cellular vulnerability to stressors, we propose that dopamine-induced autophagic inhibition could explain the selective degeneration of PD dopaminergic neurons.

Neurotrophic factors and Parkinson's disease: the emergence of a new player?

The administration of neurotrophic factors is a potential approach to the therapy of neurodegenerative disorders such as Parkinson's disease. However, issues relating to compound delivery and potential side effects have limited the clinical application of this treatment strategy. The identification of CDNF and MANF, which constitute a new class of neurotrophic factors active against dopaminergic neurons, may provide new hope for therapeutic approaches to neurodegenerative disorders based on neurotrophic factors or downstream components of their signaling pathways.

Alpha-synuclein involvement in hippocampal synaptic plasticity: role of NO, cGMP, cGK and CaMKII

Synaptic plasticity involves a series of coordinate changes occurring both pre- and postsynaptically, of which alpha-synuclein is an integral part. We have investigated on mouse primary hippocampal neurons in culture whether redistribution of alpha-synuclein during plasticity involves retrograde signaling activation through nitric oxide (NO), cGMP, cGMP-dependent protein kinase (cGK) and calmodulin-dependent protein kinase II. We have found that deletion of the alpha-synuclein gene blocks both the long-lasting enhancement of evoked and miniature transmitter release and the increase in the number of functional presynaptic boutons evoked through the NO donor, DEA/NO, and the cGMP analog, 8-Br-cGMP. In agreement with these findings both DEA/NO and 8-Br-cGMP were capable of producing a long-lasting increase in number of clusters for alpha-synuclein through activation of soluble guanylyl cyclase, cGK and calcium/calmodulin-dependent protein kinase IIalpha. Thus, our results suggest that NO, cGMP, GMP-dependent protein kinase and calmodulin-dependent protein kinase II play a key role in the redistribution of alpha-synuclein during plasticity.

alpha-Synuclein produces a long-lasting increase in neurotransmitter release

Wild-type alpha-synuclein, a protein of unknown function, has received much attention because of its involvement in a series of diseases that are known as synucleinopathies. We find that long-lasting potentiation of synaptic transmission between cultured hippocampal neurons is accompanied by an increase in the number of alpha-synuclein clusters. Conversely, suppression of alpha-synuclein expression through antisense nucleotide and knockout techniques blocks the potentiation, as well as the glutamate-induced increase in presynaptic functional bouton number. Consistent with these findings, alpha-synuclein introduction into the presynaptic neuron of a pair of monosynaptically connected cells causes a rapid and long-lasting enhancement of synaptic transmission, and rescues the block of potentiation in alpha-synuclein null mouse cultures. Also, we report that the application of nitric oxide (NO) increases the number of alpha-synuclein clusters, and inhibitors of NO-synthase block this increase, supporting the hypothesis that NO is involved in the enhancement of the number of alpha-synuclein clusters. Thus, alpha-synuclein is involved in synaptic plasticity by augmenting transmitter release from the presynaptic terminal.

Regulation of the development of mesencephalic dopaminergic systems by the selective expression of glial cell line-derived neurotrophic factor in their targets

Glial cell line-derived neurotrophic factor (GDNF) has been shown to protect and restore dopamine (DA) neurons in injury models and is being evaluated for the treatment of Parkinson's disease. Nevertheless, little is known of its physiological role. We have shown that GDNF suppresses apoptosis in DA neurons of the substantia nigra (SN) postnatally both in vitro and during their first phase of natural cell death in vivo. Furthermore, intrastriatal injection of neutralizing antibodies augments cell death, suggesting that endogenous GDNF plays a role as a target-derived factor. Such a role would predict that overexpression of GDNF in striatum would increase the surviving number of SN DA neurons. To test this hypothesis, we used the tetracycline-dependent transcription activator (tTA)/tTA-responsive promoter system to create mice that overexpress GDNF selectively in the striatum, cortex, and hippocampus. These mice demonstrate an increased number of SN DA neurons after the first phase of natural cell death. However, this increase does not persist into adulthood. As adults, these mice also do not have increased dopaminergic innervation of the striatum. They do, however, demonstrate increased numbers of ventral tegmental area (VTA) neurons and increased innervation of the cortex. This morphologic phenotype is associated with an increased locomotor response to amphetamine. We conclude that striatal GDNF is necessary and sufficient to regulate the number of SN DA neurons surviving the first phase of natural cell death, but it is not sufficient to increase their final adult number. GDNF in VTA targets, however, is sufficient to regulate the adult number of DA neurons.

Parkinson's disease: mechanisms and models

Parkinson's disease (PD) results primarily from the death of dopaminergic neurons in the substantia nigra. Current PD medications treat symptoms; none halt or retard dopaminergic neuron degeneration. The main obstacle to developing neuroprotective therapies is a limited understanding of the key molecular events that provoke neurodegeneration. The discovery of PD genes has led to the hypothesis that misfolding of proteins and dysfunction of the ubiquitin-proteasome pathway are pivotal to PD pathogenesis. Previously implicated culprits in PD neurodegeneration, mitochondrial dysfunction and oxidative stress, may also act in part by causing the accumulation of misfolded proteins, in addition to producing other deleterious events in dopaminergic neurons. Neurotoxin-based models (particularly MPTP) have been important in elucidating the molecular cascade of cell death in dopaminergic neurons. PD models based on the manipulation of PD genes should prove valuable in elucidating important aspects of the disease, such as selective vulnerability of substantia nigra dopaminergic neurons to the degenerative process.

Resistance of alpha -synuclein null mice to the parkinsonian neurotoxin MPTP

Parkinson's disease (PD) is most commonly a sporadic illness, and is characterized by degeneration of substantia nigra dopamine (DA) neurons and abnormal cytoplasmic aggregates of alpha-synuclein. Rarely, PD may be caused by missense mutations in alpha-synuclein. MPTP, a neurotoxin that inhibits mitochondrial complex I, is a prototype for an environmental cause of PD because it produces a pattern of DA neurodegeneration that closely resembles the neuropathology of PD. Here we show that alpha-synuclein null mice display striking resistance to MPTP-induced degeneration of DA neurons and DA release, and this resistance appears to result from an inability of the toxin to inhibit complex I. Contrary to predictions from in vitro data, this resistance is not due to abnormalities of the DA transporter, which appears to function normally in alpha-synuclein null mice. Our results suggest that some genetic and environmental factors that increase susceptibility to PD may interact with a common molecular pathway, and represent the first demonstration that normal alpha-synuclein function may be important to DA neuron viability.

[Therapeutic results in advanced ovarian cancer]

From 1977 to 1981 39 patients with advanced ovarian carcinoma (stage III, IV, and relapses) were treated at the department of oncology. From 1977 to 1979 we followed to a great extent the ECOG protocol (EST 2875) which means combination chemotherapy by alternating cycles. Since 1980 we used for treatment the PAC I regimen. There was no obvious difference between the therapeutic results of regimen 1 (MTX/Thio followed by 5FU/CTX) and regimen 2 (MTX/Thio followed by VCR/ADM/5FU/CTX). The greatest complete remission rate (confirmed by a second-look laparotomy) was obtained by regimen 3 (PAC I). In 8 cases PAC I was used as a second line treatment. Only 3 partial remissions were seen.