Repurposing Immunomodulatory Imide Drugs (IMiDs) in Neuropsychiatric and Neurodegenerative Disorders

Neuroinflammation represents a common trait in the pathology and progression of the major psychiatric and neurodegenerative disorders. Neuropsychiatric disorders have emerged as a global crisis, affecting 1 in 4 people, while neurological disorders are the second leading cause of death in the elderly population worldwide (WHO, 2001; GBD 2016 Neurology Collaborators, 2019). However, there remains an immense deficit in availability of effective drug treatments for most neurological disorders. In fact, for disorders such as depression, placebos and behavioral therapies have equal effectiveness as antidepressants. For neurodegenerative diseases such as Parkinson’s disease and Alzheimer’s disease, drugs that can prevent, slow, or cure the disease have yet to be found. Several non-traditional avenues of drug target identification have emerged with ongoing neurological disease research to meet the need for novel and efficacious treatments. Of these novel avenues is that of neuroinflammation, which has been found to be involved in the progression and pathology of many of the leading neurological disorders. Neuroinflammation is characterized by glial inflammatory factors in certain stages of neurological disorders. Although the meta-analyses have provided evidence of genetic/proteomic upregulation of inflammatory factors in certain stages of neurological disorders. Although the mechanisms underpinning the connections between neuroinflammation and neurological disorders are unclear, and meta-analysis results have shown high sensitivity to factors such as disorder severity and sample type, there is significant evidence of neuroinflammation associations across neurological disorders. In this review, we summarize the role of neuroinflammation in psychiatric disorders such as major depressive disorder, generalized anxiety disorder, post-traumatic stress disorder, and bipolar disorder, as well as in neurodegenerative disorders, such as Parkinson’s disease and Alzheimer’s disease, and introduce current research on the potential of immunomodulatory imide drugs (IMiDs) as a new treatment strategy for these disorders

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation

Stable Heterogeneity for the Production of Diffusible Factors in Cell Populations

The production of diffusible molecules that promote survival and growth is common in bacterial and eukaryotic cell populations, and can be considered a form of cooperation between cells. While evolutionary game theory shows that producers and non-producers can coexist in well-mixed populations, there is no consensus on the possibility of a stable polymorphism in spatially structured populations where the effect of the diffusible molecule extends beyond one-step neighbours. I study the dynamics of biological public goods using an evolutionary game on a lattice, taking into account two assumptions that have not been considered simultaneously in existing models: that the benefit of the diffusible molecule is a non-linear function of its concentration, and that the molecule diffuses according to a decreasing gradient. Stable coexistence of producers and non-producers is observed when the benefit of the molecule is a sigmoid function of its concentration, while strictly diminishing returns lead to coexistence only for very specific parameters and linear benefits never lead to coexistence. The shape of the diffusion gradient is largely irrelevant and can be approximated by a step function. Since the effect of a biological molecule is generally a sigmoid function of its concentration (as described by the Hill equation), linear benefits or strictly diminishing returns are not an appropriate approximations for the study of biological public goods. A stable polymorphism of producers and non-producers is in line with the predictions of evolutionary game theory and likely to be common in cell populations

Long-term (trophic) purinergic signalling: purinoceptors control cell proliferation, differentiation and death

The purinergic signalling system, which uses purines and pyrimidines as chemical transmitters, and purinoceptors as effectors, is deeply rooted in evolution and development and is a pivotal factor in cell communication. The ATP and its derivatives function as a 'danger signal' in the most primitive forms of life. Purinoceptors are extraordinarily widely distributed in all cell types and tissues and they are involved in the regulation of an even more extraordinary number of biological processes. In addition to fast purinergic signalling in neurotransmission, neuromodulation and secretion, there is long-term (trophic) purinergic signalling involving cell proliferation, differentiation, motility and death in the development and regeneration of most systems of the body. In this article, we focus on the latter in the immune/defence system, in stratified epithelia in visceral organs and skin, embryological development, bone formation and resorption, as well as in cancer. Cell Death and Disease (2010) 1, e9; doi:10.1038/cddis.2009.11; published online 14 January 201

GRMA: Generalized Range Move Algorithms for the efficient optimization of MRFs

Markov Random Fields (MRF) have become an important tool for many vision applications, and the optimization of MRFs is a problem of fundamental importance. Recently, Veksler and Kumar et al. proposed the range move algorithms, which are some of the most successful optimizers. Instead of considering only two labels as in previous move-making algorithms, they explore a large search space over a range of labels in each iteration, and significantly outperform previous move-making algorithms. However, two problems have greatly limited the applicability of range move algorithms: 1) They are limited in the energy functions they can handle (i.e., only truncated convex functions); 2) They tend to be very slow compared to other move-making algorithms (e.g., �-expansion and ��-swap). In this paper, we propose two generalized range move algorithms (GRMA) for the efficient optimization of MRFs. To address the first problem, we extend the GRMAs to more general energy functions by restricting the chosen labels in each move so that the energy function is submodular on the chosen subset. Furthermore, we provide a feasible sufficient condition for choosing these subsets of labels. To address the second problem, we dynamically obtain the iterative moves by solving set cover problems. This greatly reduces the number of moves during the optimization.We also propose a fast graph construction method for the GRMAs. Experiments show that the GRMAs offer a great speedup over previous range move algorithms, while yielding competitive solutions

Multiple Molecular Mechanisms Cause Reproductive Isolation between Three Yeast Species

Incompatibility between nuclear and mitochondrial genomes in yeast species may represent a general mechanism of reproductive isolation during yeast evolution

Benznidazole biotransformation and multiple targets in <i>Trypanosoma</i> cruzi revealed by metabolomics

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, involves administration of benznidazole (Bzn). Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active, although its mode of action is not fully understood. In the present work we used a non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Methodology/Principal findings&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols trypanothione, homotrypanothione and cysteine were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment. These metabolites included reduction products, fragments and covalent adducts of reduced Bzn linked to each of the major low molecular weight thiols: trypanothione, glutathione, γ-glutamylcysteine, glutathionylspermidine, cysteine and ovothiol A. Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI, were found within the parasites, but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions/significance&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Our data is indicative of a major role of the thiol binding capacity of Bzn reduction products in the mechanism of Bzn toxicity against T. cruzi

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Highly Diastereo- and Enantioselective CuH-Catalyzed Synthesis of 2,3-Disubstituted Indolines

A diastereo- and enantioselective CuH-catalyzed method for the preparation of highly functionalized indolines is reported. The mild reaction conditions and high degree of functional group compatibility as demonstrated with substrates bearing heterocycles, olefins, and substituted aromatic groups, renders this technique highly valuable for the synthesis of a variety of cis-2,3-disubstituted indolines in high yield and enantioeselectivity.National Institutes of Health (U.S.) (Award GM46059)Danish Council for Independent Research (Postdoctoral Fellowship