Zobrazení zdroje stránky Watkinssanchez6963

Environmental pH is a critical parameter for innumerable chemical reactions, myriad biological processes and all forms of life. The mechanisms that underlie the perception of external pH (pHe) have been elucidated in detail for bacteria, fungi and mammalian cells; however, little information is available on whether and, if so, how pHe is perceived by plants. This is particularly surprising since hydrogen ion activity of the substrate is of paramount significance for plants, governing the availability of mineral nutrients, the structure of the soil microbiome and the composition of natural plant communities. Rapid changes in soil pH require constant readjustment of nutrient acquisition strategies, which is associated with dynamic alterations in gene expression. Referring to observations made in diverse experimental set-ups that unambiguously show that pHe per se affects gene expression, we hypothesize that sensing of pHe in plants is mandatory to prioritize responses to various simultaneously received environmental cues.All crops are the product of a domestication process that started less than 12,000 years ago from one or more wild populations1,2. Farmers selected desirable phenotypic traits (such as improved energy accumulation, palatability of seeds and reduced natural shattering3) while leading domesticated populations through several more or less gradual demographic contractions2,4. As a consequence, the erosion of wild genetic variation5 is typical of modern cultivars, making them highly susceptible to pathogens, pests and environmental change6,7. The loss of genetic diversity hampers further crop improvement programmes to increase food production in a changing world, posing serious threats to food security8,9. Using both ancient and modern seeds, we analysed the temporal dynamics of genetic variation and selection during the domestication process of the common bean (Phaseolus vulgaris) in the southern Andes. Here, we show that most domestic traits were selected for before 2,500 years ago, with no or only minor loss ofweak selection pressure2 by using many phenotypically similar but genetically diverse individuals as parents. Our results imply that selection strategies during the past few centuries, as compared with earlier times, more intensively reduced genetic variation within cultivars and produced further improvements by focusing on a few plants carrying the traits of interest, at the cost of marked genetic erosion within Andean landraces.Nine different antibody-drug conjugates (ADCs) are currently approved as cancer treatments, with dozens more in preclinical and clinical development. The primary goal of ADCs is to improve the therapeutic index of antineoplastic agents by restricting their systemic delivery to cells that express the target antigen of interest. Advances in synthetic biochemistry have ushered in a new generation of ADCs, which promise to improve upon the tissue specificity and cytotoxicity of their predecessors. Many of these drugs have impressive activity against treatment-refractory cancers, although hurdles impeding their broader use remain, including systemic toxicity, inadequate biomarkers for patient selection, acquired resistance and unknown benefit in combination with other cancer therapies. Emerging evidence indicates that the efficacy of a given ADC depends on the intricacies of how the antibody, linker and payload components interact with the tumour and its microenvironment, all of which have important clinical implications. In this Review, we discuss the current state of knowledge regarding the design, mechanism of action and clinical efficacy of ADCs as well as the apparent limitations of this treatment class. We then propose a path forward by highlighting several hypotheses and novel strategies to maximize the potential benefit that ADCs can provide to patients with cancer.Reactions at the interface between water and other phases play important roles in nature and in various chemical systems. Although some experimental and theoretical studies suggest that chemical reactions at water interfaces can be different from those in bulk water-for example, 'on-water catalysis' and the activation of photochemically inert fatty acids at the air-water interface upon photoexcitation-directly investigating these differences and generating molecular-level understanding has proved difficult. Here, we report on the direct probing of a photochemical reaction occurring at the air-water interface, using ultrafast phase-sensitive interface-selective nonlinear vibrational spectroscopy. The femtosecond time-resolved data obtained clearly show that the photoionization reaction of phenol proceeds 104 times faster at the water surface than in the bulk aqueous phase (upon irradiation with photons with the same energy). This finding demonstrates that photochemical reactions at water interfaces are very different from those in bulk water, reflecting distinct reaction environments at the interface.Machine learning promises to assist physicians with predictions of mortality and of other future clinical events by learning complex patterns from historical data, such as longitudinal electronic health records. Here we show that a convolutional neural network trained on raw pixel data in 812,278 echocardiographic videos from 34,362 individuals provides superior predictions of one-year all-cause mortality. The model's predictions outperformed the widely used pooled cohort equations, the Seattle Heart Failure score (measured in an independent dataset of 2,404 patients with heart failure who underwent 3,384 echocardiograms), and a machine learning model involving 58 human-derived variables from echocardiograms and 100 clinical variables derived from electronic health records. [https://www.selleckchem.com/products/reacp53.html ReACp53] We also show that cardiologists assisted by the model substantially improved the sensitivity of their predictions of one-year all-cause mortality by 13% while maintaining prediction specificity. Large unstructured datasets may enable deep learning to improve a wide range of clinical prediction models.The stimulator of interferon genes (STING) is an endoplasmic reticulum transmembrane protein that is a target of therapeutics for infectious diseases and cancer. However, early-phase clinical trials of small-molecule STING agonists have shown limited antitumour efficacy and dose-limiting toxicity. Here, we show that a polyvalent STING agonist-a pH-sensitive polymer bearing a seven-membered ring with a tertiary amine (PC7A)-activates innate-immunity pathways through the polymer-induced formation of STING-PC7A condensates. In contrast to the natural STING ligand 2',3'-cyclic-GMP-AMP (cGAMP), PC7A stimulates the prolonged production of pro-inflammatory cytokines by binding to a non-competitive STING surface site that is distinct from the cGAMP binding pocket. PC7A induces antitumour responses that are dependent on STING expression and CD8+ T-cell activity, and the combination of PC7A and cGAMP led to synergistic therapeutic outcomes (including the activation of cGAMP-resistant STING variants) in mice bearing subcutaneous tumours and in resected human tumours and lymph nodes.