First-principles study of field emission from carbon nanotubes and graphene nanoribbons

A real-space, real-time implementation of time-dependent density functional theory is used to study electron field emission from nanostructures. Carbon nanotubes and graphene nanoribbons are used as model systems. The calculations show that carbon nanotubes with iron adsorbates have spin-polarized emission currents. Graphene nanoribbons are shown to be good field emitters with spatial variation of the emission current influenced by the presence of passivating hydroge

First-principles study of field emission from carbon nanotubes and graphene nanoribbons

A real-space, real-time implementation of time-dependent density functional theory is used to study electron field emission from nanostructures. Carbon nanotubes and graphene nanoribbons are used as model systems. The calculations show that carbon nanotubes with iron adsorbates have spin-polarized emission currents. Graphene nanoribbons are shown to be good field emitters with spatial variation of the emission current influenced by the presence of passivating hydroge

The Lantern, 2017-2018

On Dissociation • Untouchable • After Rocket Man • The Science Fair • Cardinal Rule at Stephen J. Memorial • Quentin & Sylvie • Cabello • The Get Out • Painting Day • Black, White and Grey • Family Pruning • How to Remove a Stain • Becoming Ourselves • Wonderbread U • Overture • Pescadero • Gross • Stage Fright • Lucky Daddy • Sarah • Rumble • Silvermine • The Green Iguana • A Poem for Ghost Children • A Poem for Lost Boys • Mother • Drop of Grease • Don\u27t Wanna be White • I • Amelia Earhart Disappeared Into My Vagina: An Ode to Cunts, Menstrual Cups and All Things Woman • Suburban Summer • Nightmares and Dreams Induced by My Mother • Teacups, Skins, etc. • Three Thoughts About My Bedroom • Dear Siri • 2 Queens (Beyonce in Reference to Sonia Sanchez) • Voyeurs • In Front of the Bathroom Mirror • To a Rose • Howl • Mice • Mirror • Language Accordion Volcano Mouth • Lucky Woman • Butterscotch • To Persephone • Wolf • Notes Never Passed • Topple • Bust • Kyoto • Identity • Sunflower • Tornabuoni Bubbles • Olympia • Decayed Hall • Perspectivehttps://digitalcommons.ursinus.edu/lantern/1186/thumbnail.jp

A Novel Molecular Solution for Ultraviolet Light Detection in Caenorhabditis elegans

For many organisms the ability to transduce light into cellular signals is crucial for survival. Light stimulates DNA repair and metabolism changes in bacteria, avoidance responses in single-cell organisms, attraction responses in plants, and both visual and nonvisual perception in animals. Despite these widely differing responses, in all of nature there are only six known families of proteins that can transduce light. Although the roundworm Caenorhabditis elegans has none of the known light transduction systems, we show here that C. elegans strongly accelerates its locomotion in response to blue or shorter wavelengths of light, with maximal responsiveness to ultraviolet light. Our data suggest that C. elegans uses this light response to escape the lethal doses of sunlight that permeate its habitat. Short-wavelength light drives locomotion by bypassing two critical signals, cyclic adenosine monophosphate (cAMP) and diacylglycerol (DAG), that neurons use to shape and control behaviors. C. elegans mutants lacking these signals are paralyzed and unresponsive to harsh physical stimuli in ambient light, but short-wavelength light rapidly rescues their paralysis and restores normal levels of coordinated locomotion. This light response is mediated by LITE-1, a novel ultraviolet light receptor that acts in neurons and is a member of the invertebrate Gustatory receptor (Gr) family. Heterologous expression of the receptor in muscle cells is sufficient to confer light responsiveness on cells that are normally unresponsive to light. Our results reveal a novel molecular solution for ultraviolet light detection and an unusual sensory modality in C. elegans that is unlike any previously described light response in any organism

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Modulation of TGF‐β Receptor 1 signalling in Live Cells

TGF-β negatively affects the maintenance and expansion of hematopoietic stem cells ex vivo and its inhibition has been widely studied as a treatment for numerous hematopoietic disorders and cancers. Current inhibitory strategies (small molecule ATP competitors and neutralizing antibodies) are compared to a novel cell-permeable peptide-based inhibitor of TGF-β RI. Multiple levels of assay from biochemical to functional are utilized with the aim of applying the most successful inhibitor to hematopoietic stem cell culture. The neutralizing antibody proved ineffective in the short-term biochemical assay but was extremely effective at neutralizing TGF-β signalling in proliferation and hematopoietic colony-forming cell assays with no evidence of toxicity. The small molecule inhibitors (SD-208 and Pyrazole TGF-β RI inhibitor) were equally effective at micromolar levels in all forms of assay, with SD-208 being slightly more potent. The novel peptide inhibitor proved ineffective in all assays, which is likely a result of its rapid degradation in live cells.MAS

Accuracy and Performance of Functional Parameter Estimation Using a Novel Numerical Optimization Approach for GPU-Based Kinetic Compartmental Modeling

Quantitative kinetic parameters derived from dynamic contrast-enhanced (DCE) data are dependent on signal measurement quality and choice of pharmacokinetic model. However, the fundamental optimization analysis method is equally important and its impact on pharmacokinetic parameters has been mostly overlooked. We examine the effects of those choices on accuracy and performance of parameter estimation using both computer processing unit and graphical processing unit (GPU) numerical optimization implementations and evaluate the improvements offered by a novel optimization approach. A test framework was developed where experimentally derived population-average arterial input function and randomly sampled parameter sets {Ktrans, Kep, Vb, τ} were used to generate known tissue curves. Five numerical optimization algorithms were evaluated: sequential quadratic programming, downhill simplex (Nelder–Mead), pattern search, simulated annealing, and differential evolution. This was combined with various objective function implementation details: delay approximation, discretization and varying sampling rates. Then, impact of noise and CPU/GPU implementation was tested for speed and accuracy. Finally, the optimal method was compared to conventional implementation as applied to clinical DCE computed tomography. Nelder–Mead, differential evolution and sequential quadratic programming produced good results on clean and noisy input data outperforming simulated annealing and pattern search in terms of speed and accuracy in the respective order of 10−8%, 10−7%, and ×10−6%). A novel approach for DCE numerical optimization (infinite impulse response with fractional delay approximation) was implemented on GPU for speed increase of at least 2 orders of magnitude. Applied to clinical data, the magnitude of overall parameter error was &lt;10%

First-principles study of field emission from carbon nanotubes and graphene nanoribbons

A real-space, real-time implementation of time-dependent density functional theory is used to study electron field emission from nanostructures. Carbon nanotubes and graphene nanoribbons are used as model systems. The calculations show that carbon nanotubes with iron adsorbates have spin-polarized emission currents. Graphene nanoribbons are shown to be good field emitters with spatial variation of the emission current influenced by the presence of passivating hydroge

Better Defunctionalization through Lambda Set Specialization

Higher-order functions pose a challenge for both static program analyses and optimizing compilers. To simplify the analysis and compilation of languages with higher-order functions, a rich body of prior work has proposed a variety of defunctionalization techniques, which can eliminate higher-order functions from a program by transforming the program to a semantically-equivalent first-order representation. Several modern languages take this a step further, specializing higher-order functions with respect to the functions on which they operate, and in turn allowing compilers to generate more efficient code. However, existing specializing defunctionalization techniques restrict how function values may be used, forcing implementations to fall back on costly dynamic alternatives. We propose lambda set specialization (LSS), the first specializing defunctionalization technique which imposes no restrictions on how function values may be used. We formulate LSS in terms of a polymorphic type system which tracks the flow of function values through the program, and use this type system to recast specialization of higher-order functions with respect to their arguments as a form of type monomorphization. We show that our type system admits a simple and tractable type inference algorithm, and give a formalization and fully-mechanized proof in the Isabelle/HOL proof assistant showing soundness and completeness of the type inference algorithm with respect to the type system. To show the benefits of LSS, we evaluate its impact on the run time performance of code generated by the MLton compiler for Standard ML, the OCaml compiler, and the new Morphic functional programming language. We find that pre-processing with LSS achieves run time speedups of up to 6.85x under MLton, 3.45x for OCaml, and 78.93x for Morphic