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    121922 research outputs found

    Getting Away with It (Or Not): The Social Control of Organizational Deviance

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    Mens, Manus, and Medieval Literature at MIT

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    This brief essay describes a few things I've learned pedagogically from students and colleagues in STEM, with examples of how I've brought those perspectives in the classroom. It concludes with some reflections on how those pedagogical experiences have informed my recent research

    Stanley Wilfred Chambers (1890-1967) Biography

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    The prebiotic emergence of biological evolution.

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    The origin of life must have been preceded by Darwin-like evolutionary dynamics that could propagate it. How did that adaptive dynamics arise? And from what prebiotic molecules? Using evolutionary invasion analysis, we develop a universal framework for describing any origin story for evolutionary dynamics. We find that cooperative autocatalysts, i.e. autocatalysts whose per-unit reproductive rate grows as their population increases, have the special property of being able to cross a barrier that separates their initial degradation-dominated state from a growth-dominated state with evolutionary dynamics. For some model parameters, this leap to persistent propagation is likely, not rare. We apply this analysis to the Foldcat Mechanism, wherein peptides fold and help catalyse the elongation of each other. Foldcats are found to have cooperative autocatalysis and be capable of emergent evolutionary dynamics

    Introducing Mplots: scaling time series recurrence plots to massive datasets

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    Abstract: Time series similarity matrices (informally, recurrence plots or dot-plots), are useful tools for time series data mining. They can be used to guide data exploration, and various useful features can be derived from them and then fed into downstream analytics. However, time series similarity matrices suffer from very poor scalability, taxing both time and memory requirements. In this work, we introduce novel ideas that allow us to scale the largest time series similarity matrices that can be examined by several orders of magnitude. The first idea is a novel algorithm to compute the matrices in a way that removes dependency on the subsequence length. This algorithm is so fast that it allows us to now address datasets where the memory limitations begin to dominate. Our second novel contribution is a multiscale algorithm that computes an approximation of the matrix appropriate for the limitations of the user’s memory/screen-resolution, then performs a local, just-in-time recomputation of any region that the user wishes to zoom-in on. Given that this largely removes time and space barriers, human visual attention then becomes the bottleneck. We further introduce algorithms that search massive matrices with quadrillions of cells and then prioritize regions for later examination by either humans or algorithms. We will demonstrate the utility of our ideas for data exploration, segmentation, and classification in domains as diverse as astronomy, bioinformatics, entomology, and wildlife monitoring

    Ultrasonic Cigarettes: Chemicals and Cytotoxicity are Similar to Heated-Coil Pod-Style Electronic Cigarettes.

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    Our purpose was to test the hypothesis that ultrasonic cigarettes (u-cigarettes), which operate at relatively low temperatures, produce aerosols that are less harmful than heated-coil pod-style electronic cigarettes (e-cigarettes). The major chemicals in SURGE u-cigarette fluids and aerosols were quantified, their cytotoxicity and cellular effects were assessed, and a Margin of Exposure risk assessment was performed on chemicals in SURGE fluids. Four SURGE u-cigarette flavor variants (Blueberry Ice, Watermelon Ice, Green Mint, and Polar Mint) were evaluated. Flavor chemicals were quantified in fluids and aerosols using gas chromatography/mass spectrometry. Cytotoxicity and cell dynamics were assessed using the MTT assay, live-cell imaging, and fluorescence microscopy. WS-23 (a coolant) and total flavor chemical concentrations in SURGE were similar to e-cigarettes, while SURGE nicotine concentrations (13-19 mg/mL) were lower than many fourth generation e-cigarettes. Transfer efficiencies of dominant chemicals to aerosols in SURGE ranged from 44-100%. SURGE fluids and aerosols had four dominant flavor chemicals (>1 mg/mL). Toxic aldehydes were usually higher in SURGE aerosols than in SURGE fluids. SURGE fluids and aerosols had aldehyde concentrations significantly higher than pod-style e-cigarettes. Chemical constituents, solvent ratios, and aldehydes varied among SURGE flavor variants. SURGE fluids and aerosols inhibited cell growth and mitochondrial reductases, produced attenuated and round cells, and depolymerized actin filaments, effects that depended on pod flavor, chemical constituents, and concentration. The MOEs for nicotine, WS-23, and propylene glycol were <100 based on consumption of 1-2 SURGE u-cigarettes/day. Replacing the heating coil with a sonicator did not eliminate chemicals, including aldehydes, in aerosols or diminish toxicity in comparisons between SURGE and other e-cigarette pod products. The high concentrations of nicotine, WS-23, flavor chemicals, and aldehydes and the cytotoxicity of SURGE aerosols do not support the hypothesis that aerosols from u-cigarettes are less harmful than those from e-cigarettes

    HER2 overexpression in urothelial carcinoma with GATA3 and PPARG copy number gains.

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    HER2, encoded by the ERBB2 gene, is an important druggable driver of human cancer gaining increasing importance as a therapeutic target in urothelial carcinoma (UC). The genomic underpinnings of HER2 overexpression in ERBB2 nonamplified UC are poorly defined. To address this knowledge gap, we investigated 172 UC tumors from patients treated at the University of California San Francisco, using immunohistochemistry and next-generation sequencing. We found that GATA3 and PPARG copy number gains individually predicted HER2 protein expression independently of ERBB2 amplification. To validate these findings, we interrogated the Memorial Sloan Kettering/The Cancer Genome Atlas (MSK/TCGA) dataset and found that GATA3 and PPARG copy number gains individually predicted ERBB2 mRNA expression independently of ERBB2 amplification. Our findings reveal a potential link between the luminal marker HER2 and the key transcription factors GATA3 and PPARG in UC and highlight the utility of examining GATA3 and PPARG copy number states to identify UC tumors that overexpress HER2 in the absence of ERBB2 amplification. In summary, we found that an increase in copy number of GATA3 and PPARG was independently associated with higher ERBB2 expression in patient samples of UC. This finding provides a potential explanation for HER2 overexpression in UC tumors without ERBB2 amplification and a way to identify these tumors for HER2-targeted therapies

    Do Multimodal Large Language Models and Humans Ground Language Similarly?

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    Abstract: Large Language Models (LLMs) have been criticized for failing to connect linguistic meaning to the world—for failing to solve the “symbol grounding problem.” Multimodal Large Language Models (MLLMs) offer a potential solution to this challenge by combining linguistic representations and processing with other modalities. However, much is still unknown about exactly how and to what degree MLLMs integrate their distinct modalities—and whether the way they do so mirrors the mechanisms believed to underpin grounding in humans. In humans, it has been hypothesized that linguistic meaning is grounded through “embodied simulation,” the activation of sensorimotor and affective representations reflecting described experiences. Across four pre-registered studies, we adapt experimental techniques originally developed to investigate embodied simulation in human comprehenders to ask whether MLLMs are sensitive to sensorimotor features that are implied but not explicit in descriptions of an event. In Experiment 1, we find sensitivity to some features (color and shape) but not others (size, orientation, and volume). In Experiment 2, we identify likely bottlenecks to explain an MLLM’s lack of sensitivity. In Experiment 3, we find that despite sensitivity to implicit sensorimotor features, MLLMs cannot fully account for human behavior on the same task. Finally, in Experiment 4, we compare the psychometric predictive power of different MLLM architectures and find that ViLT, a single-stream architecture, is more predictive of human responses to one sensorimotor feature (shape) than CLIP, a dual-encoder architecture—despite being trained on orders of magnitude less data. These results reveal strengths and limitations in the ability of current MLLMs to integrate language with other modalities, and also shed light on the likely mechanisms underlying human language comprehension

    Exploring Subsite Selectivity within Plasmodium vivax N‑Myristoyltransferase Using Pyrazole-Derived Inhibitors

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    N-myristoyltransferase (NMT) is a promising antimalarial drug target. Despite biochemical similarities between Plasmodium vivax and human NMTs, our recent research demonstrated that high selectivity is achievable. Herein, we report PvNMT-inhibiting compounds aimed at identifying novel mechanisms of selectivity. Various functional groups are appended to a pyrazole moiety in the inhibitor to target a pocket formed beneath the peptide binding cleft. The inhibitor core group polarity, lipophilicity, and size are also varied to probe the water structure near a channel. Selectivity index values range from 0.8 to 125.3. Cocrystal structures of two selective compounds, determined at 1.97 and 2.43 Å, show that extensions bind the targeted pocket but with different stabilities. A bulky naphthalene moiety introduced into the core binds next to instead of displacing protein-bound waters, causing a shift in the inhibitor position and expanding the binding site. Our structure-activity data provide a conceptual foundation for guiding future inhibitor optimizations

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