Noise sensitivity of sub- and supercritically bifurcating patterns with group velocities close to the convective-absolute instability

The influence of small additive noise on structure formation near a forwards and near an inverted bifurcation as described by a cubic and quintic Ginzburg Landau amplitude equation, respectively, is studied numerically for group velocities in the vicinity of the convective-absolute instability where the deterministic front dynamics would empty the system.Comment: 16 pages, 7 Postscript figure

Star and Planet Formation with ALMA: an Overview

Submillimeter observations with ALMA will be the essential next step in our understanding of how stars and planets form. Key projects range from detailed imaging of the collapse of pre-stellar cores and measuring the accretion rate of matter onto deeply embedded protostars, to unravelling the chemistry and dynamics of high-mass star-forming clusters and high-spatial resolution studies of protoplanetary disks down to the 1 AU scale.Comment: Invited review, 8 pages, 5 figures; to appear in the proceedings of "Science with ALMA: a New Era for Astrophysics". Astrophysics & Space Science, in pres

Natural product derivative Gossypolone inhibits Musashi family of RNA-binding proteins

Background: The Musashi (MSI) family of RNA-binding proteins is best known for the role in post-transcriptional regulation of target mRNAs. Elevated MSI1 levels in a variety of human cancer are associated with up-regulation of Notch/Wnt signaling. MSI1 binds to and negatively regulates translation of Numb and APC (adenomatous polyposis coli), negative regulators of Notch and Wnt signaling respectively. Methods: Previously, we have shown that the natural product (-)-gossypol as the first known small molecule inhibitor of MSI1 that down-regulates Notch/Wnt signaling and inhibits tumor xenograft growth in vivo. Using a fluorescence polarization (FP) competition assay, we identified gossypolone (Gn) with a > 20-fold increase in Ki value compared to (-)-gossypol. We validated Gn binding to MSI1 using surface plasmon resonance, nuclear magnetic resonance, and cellular thermal shift assay, and tested the effects of Gn on colon cancer cells and colon cancer DLD-1 xenografts in nude mice. Results: In colon cancer cells, Gn reduced Notch/Wnt signaling and induced apoptosis. Compared to (-)-gossypol, the same concentration of Gn is less active in all the cell assays tested. To increase Gn bioavailability, we used PEGylated liposomes in our in vivo studies. Gn-lip via tail vein injection inhibited the growth of human colon cancer DLD-1 xenografts in nude mice, as compared to the untreated control (P < 0.01, n = 10). Conclusion: Our data suggest that PEGylation improved the bioavailability of Gn as well as achieved tumor-targeted delivery and controlled release of Gn, which enhanced its overall biocompatibility and drug efficacy in vivo. This provides proof of concept for the development of Gn-lip as a molecular therapy for colon cancer with MSI1/MSI2 overexpression

Natural product (-)-gossypol inhibits colon cancer cell growth by targeting RNA-binding protein Musashi-1

Musashi-1 (MSI1) is an RNA-binding protein that acts as a translation activator or repressor of target mRNAs. The best-characterized MSI1 target is Numb mRNA, whose encoded protein negatively regulates Notch signaling. Additional MSI1 targets include the mRNAs for the tumor suppressor protein APC that regulates Wnt signaling and the cyclin-dependent kinase inhibitor P21WAF-1. We hypothesized that increased expression of NUMB, P21 and APC, through inhibition of MSI1 RNA-binding activity might be an effective way to simultaneously downregulate Wnt and Notch signaling, thus blocking the growth of a broad range of cancer cells. We used a fluorescence polarization assay to screen for small molecules that disrupt the binding of MSI1 to its consensus RNA binding site. One of the top hits was (-)-gossypol (Ki = 476 ± 273 nM), a natural product from cottonseed, known to have potent anti-tumor activity and which has recently completed Phase IIb clinical trials for prostate cancer. Surface plasmon resonance and nuclear magnetic resonance studies demonstrate a direct interaction of (-)-gossypol with the RNA binding pocket of MSI1. We further showed that (-)-gossypol reduces Notch/Wnt signaling in several colon cancer cell lines having high levels of MSI1, with reduced SURVIVIN expression and increased apoptosis/autophagy. Finally, we showed that orally administered (-)-gossypol inhibits colon cancer growth in a mouse xenograft model. Our study identifies (-)-gossypol as a potential small molecule inhibitor of MSI1-RNA interaction, and suggests that inhibition of MSI1's RNA binding activity may be an effective anti-cancer strategy

Neuroimaging-based classification of PTSD using data-driven computational approaches: a multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.Stress-related psychiatric disorders across the life spa

Wave-like patterns of plant phenology determine ungulate movement tactics

Animals exhibit a diversity of movement tactics [1]. Tracking resources that change across space and time is predicted to be a fundamental driver of animal movement [2]. For example, some migratory ungulates (i.e., hooved mammals) closely track the progression of highly nutritious plant green-up, a phenomenon called ‘‘green-wave surfing’’ [3–5]. Yet general principles describing how the dynamic nature of resources determine movement tactics are lacking [6]. We tested an emerging theory that predicts surfing and the existence of migratory behavior will be favored in environments where green-up is fleeting and moves sequentially across large landscapes (i.e., wave-like green-up) [7]. Landscapes exhibiting wave-like patterns of greenup facilitated surfing and explained the existence of migratory behavior across 61 populations of four ungulate species on two continents (n = 1,696 individuals). At the species level, foraging benefits were equivalent between tactics, suggesting that each movement tactic is fine-tuned to local patterns of plant phenology. For decades, ecologists have sought to understand how animals move to select habitat, commonly defining habitat as a set of static patches [8, 9]. Our findings indicate that animal movement tactics emerge as a function of the flux of resources across space and time, underscoring the need to redefine habitat to include its dynamic attributes. As global habitats continue to be modified by anthropogenic disturbance and climate change [10], our synthesis provides a generalizable framework to understand how animal movement will be influenced by altered patterns of resource phenology

Multiplex families with epilepsy: success of clinical and molecular genetic characterization

Objective: To analyze the clinical syndromes and inheritance patterns of multiplex families with epilepsy toward the ultimate aim of uncovering the underlying molecular genetic basis. Methods: Following the referral of families with 2 or more relatives with epilepsy, individuals were classified into epilepsy syndromes. Families were classified into syndromes where at least 2 family members had a specific diagnosis. Pedigrees were analyzed and molecular genetic studies were performed as appropriate. Results: A total of 211 families were ascertained over an 11-year period in Israel. A total of 169 were classified into broad familial epilepsy syndrome groups: 61 generalized, 22 focal, 24 febrile seizure syndromes, 33 special syndromes, and 29 mixed. A total of 42 families remained unclassified. Pathogenic variants were identified in 49/211 families (23%). The majority were found in established epilepsy genes (e.g., SCN1A, KCNQ2, CSTB), but in 11 families, this cohort contributed to the initial discovery (e.g., KCNT1, PCDH19, TBC1D24). We expand the phenotypic spectrum of established epilepsy genes by reporting a familial LAMC3 homozygous variant, where the predominant phenotype was epilepsy with myoclonic-atonic seizures, and a pathogenic SCN1A variant in a family where in 5 siblings the phenotype was broadly consistent with Dravet syndrome, a disorder that usually occurs sporadically. Conclusion: A total of 80% of families were successfully classified, with pathogenic variants identified in 23%. The successful characterization of familial electroclinical and inheritance patterns has highlighted the value of studying multiplex families and their contribution towards uncovering the genetic basis of the epilepsies.Zaid Afawi, Karen L. Oliver, Sara Kivity, Aziz Mazarib, Ilan Blatt, Miriam Y. Neufeld, Katherine L. Helbig, Hadassa Goldberg-Stern, Adel J. Misk, Rachel Straussberg, Simri Walid, Muhammad Mahajnah, Tally Lerman-Sagie, Bruria Ben-Zeev, Esther Kahana, Rafik Masalha, Uri Kramer, Dana Ekstein, Zamir Shorer, Robyn H. Wallace, Marie Mangelsdorf, James N. MacPherson, Gemma L. Carvill, Heather C. Mefford, Graeme D. Jackson, Ingrid E. Scheffer, Melanie Bahlo, Jozef Gecz, Sarah E. Heron, Mark Corbett, John C. Mulley, Leanne M. Dibbens, Amos D. Korczyn and Samuel F. Berkovi