Generative Modeling via Hierarchical Tensor Sketching

We propose a hierarchical tensor-network approach for approximating high-dimensional probability density via empirical distribution. This leverages randomized singular value decomposition (SVD) techniques and involves solving linear equations for tensor cores in this tensor network. The complexity of the resulting algorithm scales linearly in the dimension of the high-dimensional density. An analysis of estimation error demonstrates the effectiveness of this method through several numerical experiments

Seasonality in the Anthropocene: on the construction of Southeast Asia’s 'haze season'

The widespread burning of tropical peatlands across regions of Malaysia and Indonesia is now considered an annual event in equatorial Southeast Asia. The fires cause poor air quality (‘haze’) across the region, affecting the health of millions, but little has been written about how people in Southeast Asia make sense of this recurring phenomenon. In this paper, we investigate the emergent social construction of the ‘haze season’. Borrowing from anthropology literature, we define ‘seasons’ as a social construct that enables societies to organise their livelihoods around the expectation of recurring phenomena. The construction of ‘haze season’, in turn, reflects ongoing deliberation and contestation of the societal perception of and reaction to the causes and effects of haze. To do that, we analysed more than 35,000 news articles published in Indonesia, Malaysia and Singapore to investigate the timing of haze season reporting and key themes associated with the season. Deploying keyness analysis and structural topic modelling (STM), we find a strong distinction between the themes of articles written about the ‘haze season’ and articles that simply refer to the haze problem alone. Articles that mention ‘haze’ but not ‘haze season’ focus on the root causes of the haze crisis – peatland fires in Indonesia, oil palm plantations, deforestation – as well as geopolitical cooperation to prevent fires (e.g., through ASEAN). We found that the ‘haze season’ articles have a strong association with the effects of the haze crisis, particularly during the haze season months (June to October), suggesting that seasonality plays a role in adaptation behaviour. Outside of the haze season months, articles focus more on haze mitigation and associated political action. As a season that has emerged entirely as the result of human activity, affecting hundreds of millions of people over a spatial extent of millions of square kilometres, we argue that the ‘haze season’ is a ‘Season of the Anthropocene’. We suggest that we should expect more seasons of the Anthropocene as environmental crises and our response to those crises become more acute through this century

Microfiber Drug/Gene Delivery Platform for Study of Myelination

Our ability to rescue functional deficits after demyelinating diseases or spinal cord injuries is limited by our lack of understanding of the complex remyelination process, which is crucial to functional recovery. In this study, we developed an electrospun suspended poly(ε-caprolactone) microfiber platform to enable the screening of therapeutics for remyelination. As a proof of concept, this platform employed scaffold-mediated non-viral delivery of a microRNA (miR) cocktail to promote oligodendrocyte precursor cells (OPCs) differentiation and myelination. We observed enhanced OPCs differentiation when the cells were transfected with miR-219 and miR-338 on the microfiber substrates. Moreover, miRs promoted the formation of MBP+ tubular extensions around the suspended fibers, which was indicative of myelination, instead of flat myelin membranes on 2D substrates. In addition, OPCs that were transfected with the cocktail of miRs formed significantly longer and larger amounts of MBP+ extensions. Taken together, these results demonstrate the efficacy of this functional screening platform for understanding myelination.MOE (Min. of Education, S’pore)NMRC (Natl Medical Research Council, S’pore)Accepted versio

A BAYESIAN GRAPHICAL MODELING APPROACH TO MICRORNA REGULATORY NETWORK INFERENCE

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in animals and plants. Genes regulated by miRNAs are called targets. Typically, methods for target prediction are based solely on sequence data and on the structure information. In this paper we propose a Bayesian graphical modeling approach that infers the miRNA regulatory network by integrating expression levels of miRNAs with their potential mRNA targets and, via the prior probability model, with their sequence/structure information. We use a directed graphical model with a particular structure adapted to our data based on biological considerations. We then achieve network inference using stochastic search methods for variable selection that allow us to explore the huge model space via MCMC. A time-dependent coefficients model is also implemented. We consider experimental data from a study on a very well-known developmental toxicant causing neural tube defects, hyperthermia. Some of the pairs of target gene and miRNA we identify seem very plausible and warrant future investigation. Our proposed method is general and can be easily applied to other types of network inference by integrating multiple data sources.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS360 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Biomimicking Fiber Platform with Tunable Stiffness to Study Mechanotransduction Reveals Stiffness Enhances Oligodendrocyte Differentiation but Impedes Myelination through YAP-dependent Regulation

A key hallmark of many diseases, especially those in the central nervous system (CNS), is the change in tissue stiffness due to inflammation and scarring. However, how such changes in microenvironment affect the regenerative process remains poorly understood. Here, a biomimicking fiber platform that provides independent variation of fiber structural and intrinsic stiffness is reported. To demonstrate the functionality of these constructs as a mechanotransduction study platform, these substrates are utilized as artificial axons and the effects of axon structural versus intrinsic stiffness on CNS myelination are independently analyzed. While studies have shown that substrate stiffness affects oligodendrocyte differentiation, the effects of mechanical stiffness on the final functional state of oligodendrocyte (i.e., myelination) has not been shown prior to this. Here, it is demonstrated that a stiff mechanical microenvironment impedes oligodendrocyte myelination, independently and distinctively from oligodendrocyte differentiation. Yes-associated protein is identified to be involved in influencing oligodendrocyte myelination through mechanotransduction. The opposing effects on oligodendrocyte differentiation and myelination provide important implications for current work screening for promyelinating drugs, since these efforts have focused mainly on promoting oligodendrocyte differentiation. Thus, the platform may have considerable utility as part of a drug discovery program in identifying molecules that promote both differentiation and myelination

Bioprospecting metagenomics of decaying wood: mining for new glycoside hydrolases

<p>Abstract</p> <p>Background</p> <p>To efficiently deconstruct recalcitrant plant biomass to fermentable sugars in industrial processes, biocatalysts of higher performance and lower cost are required. The genetic diversity found in the metagenomes of natural microbial biomass decay communities may harbor such enzymes. Our goal was to discover and characterize new glycoside hydrolases (GHases) from microbial biomass decay communities, especially those from unknown or never previously cultivated microorganisms.</p> <p>Results</p> <p>From the metagenome sequences of an anaerobic microbial community actively decaying poplar biomass, we identified approximately 4,000 GHase homologs. Based on homology to GHase families/activities of interest and the quality of the sequences, candidates were selected for full-length cloning and subsequent expression. As an alternative strategy, a metagenome expression library was constructed and screened for GHase activities. These combined efforts resulted in the cloning of four novel GHases that could be successfully expressed in <it>Escherichia coli</it>. Further characterization showed that two enzymes showed significant activity on <it>p</it>-nitrophenyl-α-<smcaps>L</smcaps>-arabinofuranoside, one enzyme had significant activity against <it>p</it>-nitrophenyl-β-<smcaps>D</smcaps>-glucopyranoside, and one enzyme showed significant activity against <it>p</it>-nitrophenyl-β-<smcaps>D</smcaps>-xylopyranoside. Enzymes were also tested in the presence of ionic liquids.</p> <p>Conclusions</p> <p>Metagenomics provides a good resource for mining novel biomass degrading enzymes and for screening of cellulolytic enzyme activities. The four GHases that were cloned may have potential application for deconstruction of biomass pretreated with ionic liquids, as they remain active in the presence of up to 20% ionic liquid (except for 1-ethyl-3-methylimidazolium diethyl phosphate). Alternatively, ionic liquids might be used to immobilize or stabilize these enzymes for minimal solvent processing of biomass.</p

A Recurrent Mutation in PARK2 Is Associated with Familial Lung Cancer

PARK2, a gene associated with Parkinson disease, is a tumor suppressor in human malignancies. Here, we show that c.823C>T (p.Arg275Trp), a germline mutation in PARK2, is present in a family with eight cases of lung cancer. The resulting amino acid change, p.Arg275Trp, is located in the highly conserved RING finger 1 domain of PARK2, which encodes an E3 ubiquitin ligase. Upon further analysis, the c.823C>T mutation was detected in three additional families affected by lung cancer. The effect size for PARK2 c.823C>T (odds ratio = 5.24) in white individuals was larger than those reported for variants from lung cancer genome-wide association studies. These data implicate this PARK2 germline mutation as a genetic susceptibility factor for lung cancer. Our results provide a rationale for further investigations of this specific mutation and gene for evaluation of the possibility of developing targeted therapies against lung cancer in individuals with PARK2 variants by compensating for the loss-of-function effect caused by the associated variation

Human papillomavirus infection in “young” versus “old” patients with squamous cell carcinoma of the head and neck

Background Human papillomavirus (HPV) represents a potential risk factor for squamous cell cancer of the head and neck (SCCHN). We evaluated the prevalence of HPV DNA in patients with SCCHN diagnosed at the University of Michigan from 1994–1996. Methods Patients were stratified by age at diagnosis as “young” (50 years; median, 66). Fourteen “young” and 14 “old” were matched for tumor site, and 4 additional “old” patients were included. Specimens were analyzed by polymerase chain reaction for HPV DNA using 2 sets of consensus primers. HPV sequences were confirmed by Southern blot hybridization and typed with type-specific probes. Results Overall, 15 of 32 (46.9%) samples contained HPV sequences. HPV 16 was detected in 9 of 15 (60%), HPV-18 in 1 of 15 (6.6%), and 5 of 15 (33.3%) remained untyped by multiple methods. When stratified, 7 of 14 (50%) “young” were HPV-positive compared with 8 of 18 (44.4%) “old” ( p = .76). Survival in patients with HPV-positive SCCHN was significantly longer than that for HPV-negative patients. Conclusions The incidence of HPV in “young” versus “old” is not significantly different, suggesting similar roles for both groups. Patients with HPV-positive tumors may have a survival advantage relative to patients with HPV-negative tumors. © 2000 John Wiley & Sons, Inc. Head Neck 22: 649–657, 2000.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/35115/1/2_ftp.pd