Fast Local Computation Algorithms

For input $x$, let $F(x)$ denote the set of outputs that are the "legal" answers for a computational problem $F$. Suppose $x$ and members of $F(x)$ are so large that there is not time to read them in their entirety. We propose a model of {\em local computation algorithms} which for a given input $x$, support queries by a user to values of specified locations $y_i$ in a legal output $y \in F(x)$. When more than one legal output $y$ exists for a given $x$, the local computation algorithm should output in a way that is consistent with at least one such $y$. Local computation algorithms are intended to distill the common features of several concepts that have appeared in various algorithmic subfields, including local distributed computation, local algorithms, locally decodable codes, and local reconstruction. We develop a technique, based on known constructions of small sample spaces of $k$-wise independent random variables and Beck's analysis in his algorithmic approach to the Lov{\'{a}}sz Local Lemma, which under certain conditions can be applied to construct local computation algorithms that run in {\em polylogarithmic} time and space. We apply this technique to maximal independent set computations, scheduling radio network broadcasts, hypergraph coloring and satisfying $k$-SAT formulas.Comment: A preliminary version of this paper appeared in ICS 2011, pp. 223-23

Capillary condensation between disks in two dimensions

Capillary condensation between two two-dimensional wetted circular substrates (disks) is studied by an effective free energy description of the wetting interface. The interfacial free-energy potential is developed on the basis of the theory for the wetting of a single disk, where interfacial capillary fluctuations play a dominant role. A simple approximative analytical expression of the interfacial free energy is developed and is validated numerically. The capillary condensation is characterized by the analysis of the coverage of the condensed phase, its stability, and asymptotic behaviors. The theory can be applied to the description of flocculations in two-dimensional systems of colloids

Coupling shRNA screens with single-cell RNA-seq identifies a dual role for mTOR in reprogramming-induced senescence

Expression of the transcription factors OCT4, SOX2, KLF4, and cMYC (OSKM) reprograms somatic cells into induced pluripotent stem cells (iPSCs). Reprogramming is a slow and inefficient process, suggesting the presence of safeguarding mechanisms that counteract cell fate conversion. One such mechanism is senescence. To identify modulators of reprogramming-induced senescence, we performed a genome-wide shRNA screen in primary human fibroblasts expressing OSKM. In the screen, we identified novel mediators of OSKM-induced senescence and validated previously implicated genes such as CDKN1A. We developed an innovative approach that integrates single-cell RNA sequencing (scRNA-seq) with the shRNA screen to investigate the mechanism of action of the identified candidates. Our data unveiled regulation of senescence as a novel way by which mechanistic target of rapamycin (mTOR) influences reprogramming. On one hand, mTOR inhibition blunts the induction of cyclin-dependent kinase (CDK) inhibitors (CDKIs), including p16INK4a, p21CIP1, and p15INK4b, preventing OSKM-induced senescence. On the other hand, inhibition of mTOR blunts the senescence-associated secretory phenotype (SASP), which itself favors reprogramming. These contrasting actions contribute to explain the complex effect that mTOR has on reprogramming. Overall, our study highlights the advantage of combining functional screens with scRNA-seq to accelerate the discovery of pathways controlling complex phenotypes

Clearance of senescent macrophages ameliorates tumorigenesis in KRAS-driven lung cancer

The accumulation of senescent cells in the tumor microenvironment can drive tumorigenesis in a paracrine manner through the senescence-associated secretory phenotype (SASP). Using a new p16-FDR mouse line, we show that macrophages and endothelial cells are the predominant senescent cell types in murine KRAS-driven lung tumors. Through single cell transcriptomics, we identify a population of tumor-associated macrophages that express a unique array of pro-tumorigenic SASP factors and surface proteins and are also present in normal aged lungs. Genetic or senolytic ablation of senescent cells, or macrophage depletion, result in a significant decrease in tumor burden and increased survival in KRAS-driven lung cancer models. Moreover, we reveal the presence of macrophages with senescent features in human lung pre-malignant lesions, but not in adenocarcinomas. Taken together, our results have uncovered the important role of senescent macrophages in the initiation and progression of lung cancer, highlighting potential therapeutic avenues and cancer preventative strategies

Facing Anxiety, Growing Up. Trait Emotional Intelligence as a Mediator of the Relationship Between Self-Esteem and University Anxiety

The current study analyzed how trait emotional intelligence (trait EI) mediates the relationship between self-esteem and state anxiety and trait anxiety. The sample was composed of 153 undergraduate students from the University of Cádiz, Spain (71.9% women and 28.1% men). Students completed measures of self-esteem, state anxiety, trait anxiety, and trait EI. Mediation analyses were completed with three trait EI dimensions (EA, emotional attention; EC, emotional clarity; and MR, mood repair) as mediating variables, self-esteem as the independent variable, and state anxiety and trait anxiety as the dependent ones. Our results confirmed that self-esteem scores explained and predicted both, state and trait anxiety values (13% for state and 21% for trait anxiety). This explanatory capacity is increased by 8% when accounting for all trait EI dimensions. Considering state anxiety, the results of the direct effects showed that a decrease in their levels is predicted through the increases in the levels of both, self-esteem and MR. Regarding trait anxiety, the results of the direct effects showed that a decrease in their levels is predicted, in addition to an increment of self-esteem and MR values, by an increase of EC and a decrease of EA. Conversely, indirect effects revealed that higher levels of self-esteem were associated with worse scores in EA and worse MR, which in turn would enhance both state and trait anxiety levels. Moreover, regarding trait anxiety higher levels of self-esteem were associated with worse scores in EA and worse EC, therefore increasing trait anxiety levels. As shown, the negative association found between self-esteem and EA becomes a key element. The effect of self-esteem on EA and the influence that the latter had on EC and MR exerts an indirect mediated effect with the power to invert the influence that self-esteem wields on both types of anxiety. In this sense, the apparent protective role of self-esteem changed, turning into a risk factor that promotes higher anxiety values

A multi-targeted approach to suppress tumor-promoting inflammation

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-κB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes