1,400 research outputs found

    The Emergence of Precision Urologic Oncology: A Collaborative Review on Biomarker-driven Therapeutics

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    CONTEXT: Biomarker-driven cancer therapy, also referred to as precision oncology, has received increasing attention for its promise of improving patient outcomes by defining subsets of patients more likely to respond to various therapies. OBJECTIVES: In this collaborative review article, we examine recent literature regarding biomarker-driven therapeutics in urologic oncology, to better define the state of the field, explore the current evidence supporting utility of this approach, and gauge potential for the future. EVIDENCE ACQUISITION: We reviewed relevant literature, with a particular focus on recent studies about targeted therapy, predictors of response, and biomarker development. EVIDENCE SYNTHESIS: The recent advances in molecular profiling have led to a rapid expansion of potential biomarkers and predictive information for patients with urologic malignancies. Across disease states, distinct molecular subtypes of cancers have been identified, with the potential to inform choices of management strategy. Biomarkers predicting response to standard therapies (such as platinum-based chemotherapy) are emerging. In several malignancies (particularly renal cell carcinoma and castration-resistant prostate cancer), targeted therapy against commonly altered signaling pathways has emerged as standard of care. Finally, targeted therapy against alterations present in rare patients (less than 2%) across diseases has the potential to drastically alter patterns of care and choices of therapeutic options. CONCLUSIONS: Precision medicine has the highest potential to impact the care of patients. Prospective studies in the setting of clinical trials and standard of care therapy will help define reliable predictive biomarkers and new therapeutic targets leading to real improvement in patient outcomes. PATIENT SUMMARY: Precision oncology uses molecular information (DNA and RNA) from the individual and the tumor to match the right patient with the right treatment. Tremendous strides have been made in defining the molecular underpinnings of urologic malignancies and understanding how these predict response to treatment—this represents the future of urologic oncology

    A digital media literacy intervention increases discernment between mainstream and false news in the United States and India

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    This is the final version. Available on open access from the National Academy of Sciences via the DOI in this recordData deposition: Data files and scripts necessary to replicate the results in this article are available at the Dataverse repository at https://doi.org/10.7910/DVN/Q5QINN. The US study preanalysis plan is available at https://osf.io/u3sgc. The India study preanalysis plan is available at https://osf.io/97rnz.Widespread belief in misinformation circulating online is a critical challenge for modern societies. While research to date has focused on psychological and political antecedents to this phenomenon, few studies have explored the role of digital media literacy shortfalls. Using data from preregistered survey experiments conducted around recent elections in the United States and India, we assess the effectiveness of an intervention modeled closely on the world's largest media literacy campaign, which provided "tips" on how to spot false news to people in 14 countries. Our results indicate that exposure to this intervention reduced the perceived accuracy of both mainstream and false news headlines, but effects on the latter were significantly larger. As a result, the intervention improved discernment between mainstream and false news headlines among both a nationally representative sample in the United States (by 26.5%) and a highly educated online sample in India (by 17.5%). This increase in discernment remained measurable several weeks later in the United States (but not in India). However, we find no effects among a representative sample of respondents in a largely rural area of northern India, where rates of social media use are far lower.European Union Horizon 2020Facebook Integrity Foundational Research Award

    Nonlinear Sigma Model for Disordered Media: Replica Trick for Non-Perturbative Results and Interactions

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    In these lectures, given at the NATO ASI at Windsor (2001), applications of the replicas nonlinear sigma model to disordered systems are reviewed. A particular attention is given to two sets of issues. First, obtaining non-perturbative results in the replica limit is discussed, using as examples (i) an oscillatory behaviour of the two-level correlation function and (ii) long-tail asymptotes of different mesoscopic distributions. Second, a new variant of the sigma model for interacting electrons in disordered normal and superconducting systems is presented, with demonstrating how to reduce it, under certain controlled approximations, to known ``phase-only'' actions, including that of the ``dirty bosons'' model.Comment: 25 pages, Proceedings of the NATO ASI "Field Theory of Strongly Correlated Fermions and Bosons in Low - Dimensional Disordered Systems", Windsor, August, 2001; to be published by Kluwe

    Rare coding SNP in DZIP1 gene associated with late-onset sporadic Parkinson's disease

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    We present the first application of the hypothesis-rich mathematical theory to genome-wide association data. The Hamza et al. late-onset sporadic Parkinson's disease genome-wide association study dataset was analyzed. We found a rare, coding, non-synonymous SNP variant in the gene DZIP1 that confers increased susceptibility to Parkinson's disease. The association of DZIP1 with Parkinson's disease is consistent with a Parkinson's disease stem-cell ageing theory.Comment: 14 page

    Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees

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    Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made

    Observer-Based State Feedback for Enhanced Insulin Control of Type ‘I’ Diabetic Patients

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    During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. This paper focuses on designing a state feedback controller with observer to improve the performance of the insulin control for type ‘I’ diabetic patients. The dynamic model of glucose levels in diabetic patients is a nonlinear model. The system is a typical fourth-order single-input-single-output state space model. Using a linear time invariant controller based on an operating condition is a common method to simplify control design. On the other hand, adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This paper investigates patient models and presents a simplified control scheme using observer-based feedback controllers. By comparing different control schemes, it shows that a properly designed state feedback controller with observer can eliminate the adaptation strategy that the Proportional-Integral-Derivative (PID) controllers need to improve the control performance. Control strategies are simulated and their performance is evaluated in MATLAB and Simulink

    Separate cortical stages in amodal completion revealed by functional magnetic resonance adaptation

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    <p>Abstract</p> <p>Background</p> <p>Objects in our environment are often partly occluded, yet we effortlessly perceive them as whole and complete. This phenomenon is called visual amodal completion. Psychophysical investigations suggest that the process of completion starts from a representation of the (visible) physical features of the stimulus and ends with a completed representation of the stimulus. The goal of our study was to investigate both stages of the completion process by localizing both brain regions involved in processing the physical features of the stimulus as well as brain regions representing the completed stimulus.</p> <p>Results</p> <p>Using fMRI adaptation we reveal clearly distinct regions in the visual cortex of humans involved in processing of amodal completion: early visual cortex – presumably V1 -processes the local contour information of the stimulus whereas regions in the inferior temporal cortex represent the completed shape. Furthermore, our data suggest that at the level of inferior temporal cortex information regarding the original local contour information is not preserved but replaced by the representation of the amodally completed percept.</p> <p>Conclusion</p> <p>These findings provide neuroimaging evidence for a multiple step theory of amodal completion and further insights into the neuronal correlates of visual perception.</p

    Ultra-fast responsive colloidal-polymer composite-based volatile organic compounds (VOC) sensor using nanoscale easy tear process

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    There is an immense need for developing a simple, rapid, and inexpensive detection assay for health-care applications or monitoring environments. To address this need, a photonic crystal (PC)-based sensor has been extensively studied due to its numerous advantages such as colorimetric measurement, high sensitivity, and low cost. However, the response time of a typical PC-based sensor is relatively slow due to the presence of the inevitable upper residual layer in colloidal structures. Hence, we propose an ultra-fast responsive PC-based volatile organic compound (VOC) sensor by using a &quot;nanoscale easy tear (NET) process&quot; inspired by commercially available &quot;easy tear package&quot;. A colloidal crystal-polydimethylsiloxane (PDMS) composite can be successfully realized through nanoscale tear propagation along the interface between the outer surface of crystallized nanoparticles and bulk PDMS. The response time for VOC detection exhibits a significant decrease by allowing the direct contact with VOCs, because of perfect removal of the residual on the colloidal crystals. Moreover, vapor-phase VOCs can be monitored, which had been previously impossible. High-throughput production of the patterned colloidal crystal-polymer composite through the NET process can be applied to other multiplexed selective sensing applications or may be used for nanomolding templates
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