The Universal Statistical Structure and Scaling Laws of Chaos and Turbulence

Turbulence is a complex spatial and temporal structure created by the strong non-linear dynamics of fluid flows at high Reynolds numbers. Despite being an ubiquitous phenomenon that has been studied for centuries, a full understanding of turbulence remained a formidable challenge. Here, we introduce tools from the fields of quantum chaos and Random Matrix Theory (RMT) and present a detailed analysis of image datasets generated from turbulence simulations of incompressible and compressible fluid flows. Focusing on two observables: the data Gram matrix and the single image distribution, we study both the local and global eigenvalue statistics and compare them to classical chaos, uncorrelated noise and natural images. We show that from the RMT perspective, the turbulence Gram matrices lie in the same universality class as quantum chaotic rather than integrable systems, and the data exhibits power-law scalings in the bulk of its eigenvalues which are vastly different from uncorrelated classical chaos, random data, natural images. Interestingly, we find that the single sample distribution only appears as fully RMT chaotic, but deviates from chaos at larger correlation lengths, as well as exhibiting different scaling properties.Comment: 9 pages, 4 figure

The Underlying Scaling Laws and Universal Statistical Structure of Complex Datasets

We study universal traits which emerge both in real-world complex datasets, as well as in artificially generated ones. Our approach is to analogize data to a physical system and employ tools from statistical physics and Random Matrix Theory (RMT) to reveal their underlying structure. We focus on the feature-feature covariance matrix, analyzing both its local and global eigenvalue statistics. Our main observations are: (i) The power-law scalings that the bulk of its eigenvalues exhibit are vastly different for uncorrelated random data compared to real-world data, (ii) this scaling behavior can be completely recovered by introducing long range correlations in a simple way to the synthetic data, (iii) both generated and real-world datasets lie in the same universality class from the RMT perspective, as chaotic rather than integrable systems, (iv) the expected RMT statistical behavior already manifests for empirical covariance matrices at dataset sizes significantly smaller than those conventionally used for real-world training, and can be related to the number of samples required to approximate the population power-law scaling behavior, (v) the Shannon entropy is correlated with local RMT structure and eigenvalues scaling, and substantially smaller in strongly correlated datasets compared to uncorrelated synthetic data, and requires fewer samples to reach the distribution entropy. These findings can have numerous implications to the characterization of the complexity of data sets, including differentiating synthetically generated from natural data, quantifying noise, developing better data pruning methods and classifying effective learning models utilizing these scaling laws.Comment: 16 pages, 7 figure

Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios

Purpose: Despite the recognized clinical value of exome-based diagnostics, methods for comprehensive genomic interpretation remain immature. Diagnoses are based on known or presumed pathogenic variants in genes already associated with a similar phenotype. Here, we extend this paradigm by evaluating novel bioinformatics approaches to aid identification of new gene–disease associations. Methods: We analyzed 119 trios to identify both diagnostic genotypes in known genes and candidate genotypes in novel genes. We considered qualifying genotypes based on their population frequency and in silico predicted effects we also characterized the patterns of genotypes enriched among this collection of patients. Results: We obtained a genetic diagnosis for 29 (24%) of our patients. We showed that patients carried an excess of damaging de novo mutations in intolerant genes, particularly those shown to be essential in mice (P = 3.4 × 10−8). This enrichment is only partially explained by mutations found in known disease-causing genes. Conclusion: This work indicates that the application of appropriate bioinformatics analyses to clinical sequence data can also help implicate novel disease genes and suggest expanded phenotypes for known disease genes. These analyses further suggest that some cases resolved by whole-exome sequencing will have direct therapeutic implications

Talin1 dysfunction is genetically linked to systemic capillary leak syndrome.

Systemic capillary leak syndrome (SCLS) is a rare life-threatening disorder due to profound vascular leak. The trigger and the cause of the disease is currently unknown and there is no specific treatment. Here, we identified a rare heterozygous splice-site variant in the TLN1 gene in a familial SCLS case, suggestive of autosomal dominant inheritance with incomplete penetrance. Talin1 has a key role in cell adhesions by activating and linking integrins to the actin cytoskeleton. This variant causes in-frame skipping of exon 54 and is predicted to affect talin’s c-terminal actin binding site (ABS3). Modelling the SCLS-TLN1 variant by mimicking the actin-binding disruption in TLN1 heterozygous endothelial cells resulted in disorganized endothelial adherens junctions. Mechanistically, we established that disruption of talin’s ABS3 sequestrates talin’s interacting partner, vinculin, at cell-extracellular matrix adhesions, leading to destabilization of the endothelial barrier. We propose that pathogenic variant in TLN1 underlie SCLS, providing insight into the molecular mechanism of the disease which can be explored for future therapeutic interventions

Noncoding deletions reveal a gene that is critical for intestinal function.

Large-scale genome sequencing is poised to provide a substantial increase in the rate of discovery of disease-associated mutations, but the functional interpretation of such mutations remains challenging. Here we show that deletions of a sequence on human chromosome 16 that we term the intestine-critical region (ICR) cause intractable congenital diarrhoea in infants1,2. Reporter assays in transgenic mice show that the ICR contains a regulatory sequence that activates transcription during the development of the gastrointestinal system. Targeted deletion of the ICR in mice caused symptoms that recapitulated the human condition. Transcriptome analysis revealed that an unannotated open reading frame (Percc1) flanks the regulatory sequence, and the expression of this gene was lost in the developing gut of mice that lacked the ICR. Percc1-knockout mice displayed phenotypes similar to those observed upon ICR deletion in mice and patients, whereas an ICR-driven Percc1 transgene was sufficient to rescue the phenotypes found in mice that lacked the ICR. Together, our results identify a gene that is critical for intestinal function and underscore the need for targeted in vivo studies to interpret the growing number of clinical genetic findings that do not affect known protein-coding genes

Measuring local depletion of terrestrial game vertebrates by central-place hunters in rural Amazonia

The degree to which terrestrial vertebrate populations are depleted in tropical forests occupied by human communities has been the subject of an intense polarising debate that has important conservation implications. Conservation ecologists and practitioners are divided over the extent to which community-based subsistence offtake is compatible with ecologically functional populations of tropical forest game species. To quantify depletion envelopes of forest vertebrates around human communities, we deployed a total of 383 camera trap stations and 78 quantitative interviews to survey the peri-community areas controlled by 60 semi-subsistence communities over a combined area of over 3.2 million hectares in the Médio Juruá and Uatumã regions of Central-Western Brazilian Amazonia. Our results largely conform with prior evidence that hunting large-bodied vertebrates reduces wildlife populations near settlements, such that they are only found at a distance to settlements where they are hunted less frequently. Camera trap data suggest that a select few harvest-sensitive species, including lowland tapir, are either repelled or depleted by human communities. Nocturnal and cathemeral species were detected relatively more frequently in disturbed areas close to communities, but individual species did not necessarily shift their activity patterns. Group biomass of all species was depressed in the wider neighbourhood of urban areas rather than communities. Interview data suggest that species traits, especially group size and body mass, mediate these relationships. Large-bodied, large-group-living species are detected farther from communities as reported by experienced informants. Long-established communities in our study regions have not “emptied” the surrounding forest. Low human population density and low hunting offtake due to abundant sources of alternative aquatic protein, suggest that these communities represent a best-case scenario for sustainable hunting of wildlife for food, thereby providing a conservative assessment of game depletion. Given this ‘best-case’ camera trap and interview-based evidence for hunting depletion, regions with higher human population densities, external trade in wildlife and limited access to alternative protein will likely exhibit more severe depletion

Extra- and intra-ovarian factors in polycystic ovary syndrome: impact on oocyte maturation and embryo developmental competence

background: Polycystic ovary syndrome (PCOS) is a common metabolic dysfunction and heterogeneous endocrine disorder in women of reproductive age. Although patients with PCOS are typically characterized by increased numbers of oocytes retrieved during IVF, they are often of poor quality, leading to lower fertilization, cleavage and implantation rates, and a higher miscarriage rate. methods: For this review, we searched the database MEDLINE (1950 to January 2010) and Google for all full texts and/or abstract articles published in English with content related to oocyte maturation and embryo developmental competence. results: The search showed that alteration of many factors may directly or indirectly impair the competence of maturating oocytes through endocrine and local paracrine/autocrine actions, resulting in a lower pregnancy rate in patients with PCOS. The extra-ovarian factors identified included gonadotrophins, hyperandrogenemia and hyperinsulinemia, although intra-ovarian factors included members of the epidermal, fibroblast, insulin-like and neurotrophin families of growth factors, as well as the cytokines. conclusions: Any abnormality in the extra- and/or intra-ovarian factors may negatively affect the granulosa cell-oocyte interaction, oocyte maturation and potential embryonic developmental competence, contributing to unsuccessful outcomes for patients with PCOS who are undergoing assisted reproduction.Obstetrics & GynecologyReproductive BiologySCI(E)PubMed49REVIEW117-331

Neurodegenerative Diseases and Autophagy

Most neurodegenerative diseases are characterized by the accumulation of aggregated proteins within neurons. These aggregate-prone proteins cause toxicity, a phenomenon that is further exacerbated when there is defective protein clearance. Autophagy is an intracellular clearance pathway that can clear these protein aggregates and has been shown to be beneficial in the treatment of neurodegenerative diseases in a variety of model systems. Here, we introduce the key components of the autophagy machinery and signaling pathways that control this process and discuss the evidence that autophagic flux may be impaired and therefore a contributing factor in neurodegenerative disease pathogenesis. Finally, we review the use of autophagy upregulation as a therapeutic strategy to treat neurodegenerative disorders