582 research outputs found

    Inclusive GAN: Improving Data and Minority Coverage in Generative Models

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    Generative Adversarial Networks (GANs) have brought about rapid progress towards generating photorealistic images. Yet the equitable allocation of their modeling capacity among subgroups has received less attention, which could lead to potential biases against underrepresented minorities if left uncontrolled. In this work, we first formalize the problem of minority inclusion as one of data coverage, and then propose to improve data coverage by harmonizing adversarial training with reconstructive generation. The experiments show that our method outperforms the existing state-of-the-art methods in terms of data coverage on both seen and unseen data. We develop an extension that allows explicit control over the minority subgroups that the model should ensure to include, and validate its effectiveness at little compromise from the overall performance on the entire dataset. Code, models, and supplemental videos are available at GitHub.Comment: Accepted to ECCV'2

    Increased interferon alpha receptor 2 mRNA levels is associated with renal cell carcinoma metastasis

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    <p>Abstract</p> <p>Background</p> <p>Interferon-ฮฑ (IFN-ฮฑ) is one of the central agents in immunotherapy for renal cell carcinoma (RCC) and binds to the IFN-ฮฑ receptor (IFNAR). We investigated the role of IFNAR in RCC.</p> <p>Methods</p> <p>We quantified IFNAR mRNA expression in paired tumor and non-tumor samples from the surgical specimens of 103 consecutive patients with RCC using a real-time reverse transcription polymerase chain reaction (RT-PCR), and IFNAR2 protein using Western blotting.</p> <p>Results</p> <p>The absolute level of IFNAR1 and IFNAR2 mRNAs in tumor and non-tumor tissues did not correlate with the malignant and metastatic profiles. The relative yields of the PCR product from the tumor tissue to that from the corresponding non-tumor tissue (T/N) for the expression of IFNAR mRNAs were calculated. While the T/N ratio of IFNAR1 did not correlate with any factor, a high T/N ratio of IFNAR2 correlated with poor differentiation (<it>P </it>< 0.05), local invasion (<it>P </it>< 0.001), and metastasis (<it>P </it>< 0.0001). By multivariate analysis, a high T/N ratio of IFNAR2 predicted a shortened overall survival in all cases (<it>P </it>< 0.05) and a shorter disease-free survival in those without metastasis (M0; 68 cases, <it>P </it>< 0.05). Impressively, patients with a poorer response to IFN-ฮฑ treatment had a higher IFNAR2 T/N ratio than those who had a good response (P < 0.05). IFNAR2c protein expression was higher in the primary tumors in patients with metastases (M1; 35 cases) compared to those without ( P < 0.0001).</p> <p>Conclusion</p> <p>IFNAR2 is associated with the progression of RCC.</p

    Experimental and Computational Characterization of Biological Liquid Crystals: A Review of Single-Molecule Bioassays

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    Quantitative understanding of the mechanical behavior of biological liquid crystals such as proteins is essential for gaining insight into their biological functions, since some proteins perform notable mechanical functions. Recently, single-molecule experiments have allowed not only the quantitative characterization of the mechanical behavior of proteins such as protein unfolding mechanics, but also the exploration of the free energy landscape for protein folding. In this work, we have reviewed the current state-of-art in single-molecule bioassays that enable quantitative studies on protein unfolding mechanics and/or various molecular interactions. Specifically, single-molecule pulling experiments based on atomic force microscopy (AFM) have been overviewed. In addition, the computational simulations on single-molecule pulling experiments have been reviewed. We have also reviewed the AFM cantilever-based bioassay that provides insight into various molecular interactions. Our review highlights the AFM-based single-molecule bioassay for quantitative characterization of biological liquid crystals such as proteins

    Proteomic Analysis of Fractionated Toxoplasma Oocysts Reveals Clues to Their Environmental Resistance

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    Toxoplasma gondii is an obligate intracellular parasite that is unique in its ability to infect a broad range of birds and mammals, including humans, leading to an extremely high worldwide prevalence and distribution. This work focuses on the environmentally resistant oocyst, which is the product of sexual replication in felids and an important source of human infection. Due to the difficulty in producing and working with oocysts, relatively little is known about how this stage is able to resist extreme environmental stresses and how they initiate a new infection, once ingested. To fill this gap, the proteome of the wall and sporocyst/sporozoite fractions of mature, sporulated oocysts were characterized using one-dimensional gel electrophoresis followed by LC-MS/MS on trypsin-digested peptides. A combined total of 1021 non-redundant T. gondii proteins were identified in the sporocyst/sporozoite fraction and 226 were identified in the oocyst wall fraction. Significantly, 172 of the identified proteins have not previously been identified in Toxoplasma proteomic studies. Among these are several of interest for their likely role in conferring environmental resistance including a family of small, tyrosine-rich proteins present in the oocyst wall fractions and late embryogenesis abundant domain-containing (LEA) proteins in the cytosolic fractions. The latter are known from other systems to be key to enabling survival against desiccation

    Senescence Is More Important in the Natural Lives of Long- Than Short-Lived Mammals

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    Senescence has been widely detected among mammals, but its importance to fitness in wild populations remains controversial. According to evolutionary theories, senescence occurs at an age when selection is relatively weak, which in mammals can be predicted by adult survival rates. However, a recent analysis of senescence rates found more age-dependent mortalities in natural populations of longer lived mammal species. This has important implications to ageing research and for understanding the ecological relevance of senescence, yet so far these have not been widely appreciated. We re-address this question by comparing the mean and maximum life span of 125 mammal species. Specifically, we test the hypothesis that senescence occurs at a younger age relative to the mean natural life span in longer lived species.We show, using phylogenetically-informed generalised least squares models, a significant log-log relationship between mean life span, as calculated from estimates of adult survival for natural populations, and maximum recorded life span among mammals (R2=0.57, p<0.0001). This provides further support for a key prediction of evolutionary theories of ageing. The slope of this relationship (0.353+/-0.052 s.e.m.), however, indicated that mammals with higher survival rates have a mean life span representing a greater fraction of their potential maximum life span: the ratio of maximum to mean life span decreased significantly from >10 in short-lived to approximately 1.5 in long-lived mammal species.We interpret the ratio of maximum to mean life span to be an index of the likelihood an individual will experience senescence, which largely determines maximum life span. Our results suggest that senescence occurs at an earlier age relative to the mean life span, and therefore is experienced by more individuals and remains under selection pressure, in long- compared to short-lived mammals. A minimum rate of somatic degradation may ultimately limit the natural life span of mammals. Our results also indicate that senescence and modulating factors like oxidative stress are increasingly important to the fitness of longer lived mammals (and vice versa)

    Nano-motion Dynamics are Determined by Surface-Tethered Selectin Mechanokinetics and Bond Formation

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    The interaction of proteins at cellular interfaces is critical for many biological processes, from intercellular signaling to cell adhesion. For example, the selectin family of adhesion receptors plays a critical role in trafficking during inflammation and immunosurveillance. Quantitative measurements of binding rates between surface-constrained proteins elicit insight into how molecular structural details and post-translational modifications contribute to function. However, nano-scale transport effects can obfuscate measurements in experimental assays. We constructed a biophysical simulation of the motion of a rigid microsphere coated with biomolecular adhesion receptors in shearing flow undergoing thermal motion. The simulation enabled in silico investigation of the effects of kinetic force dependence, molecular deformation, grouping adhesion receptors into clusters, surface-constrained bond formation, and nano-scale vertical transport on outputs that directly map to observable motions. Simulations recreated the jerky, discrete stop-and-go motions observed in P-selectin/PSGL-1 microbead assays with physiologic ligand densities. Motion statistics tied detailed simulated motion data to experimentally reported quantities. New deductions about biomolecular function for P-selectin/PSGL-1 interactions were made. Distributing adhesive forces among P-selectin/PSGL-1 molecules closely grouped in clusters was necessary to achieve bond lifetimes observed in microbead assays. Initial, capturing bond formation effectively occurred across the entire molecular contour length. However, subsequent rebinding events were enhanced by the reduced separation distance following the initial capture. The result demonstrates that vertical transport can contribute to an enhancement in the apparent bond formation rate. A detailed analysis of in silico motions prompted the proposition of wobble autocorrelation as an indicator of two-dimensional function. Insight into two-dimensional bond formation gained from flow cell assays might therefore be important to understand processes involving extended cellular interactions, such as immunological synapse formation. A biologically informative in silico system was created with minimal, high-confidence inputs. Incorporating random effects in surface separation through thermal motion enabled new deductions of the effects of surface-constrained biomolecular function. Important molecular information is embedded in the patterns and statistics of motion

    Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibeltยฎ Platform

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    Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibeltยฎ) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92โ€“0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12โ€“0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure
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