Monahanwebster7753

Nonpharmaceutical interventions to control SARS-CoV-2 spread have been implemented with different intensity, timing, and impact on transmission. As a result, post-lockdown COVID-19 dynamics are heterogeneous and difficult to interpret. We describe a set of contact surveys performed in four Chinese cities (Wuhan, Shanghai, Shenzhen, and Changsha) during the pre-pandemic, lockdown and post-lockdown periods to quantify changes in contact patterns. In the post-lockdown period, the mean number of contacts increased by 5 to 17% as compared to the lockdown period. However, it remains three to seven times lower than its pre-pandemic level sufficient to control SARS-CoV-2 transmission. We find that the impact of school interventions depends nonlinearly on the intensity of other activities. When most community activities are halted, school closure leads to a 77% decrease in the reproduction number; in contrast, when social mixing outside of schools is at pre-pandemic level, school closure leads to a 5% reduction in transmission.Effectors are small, secreted proteins that promote pathogen virulence. Although key to microbial infections, unlocking the intrinsic function of effectors remains a challenge. We have previously shown that members of the fungal Avr4 effector family use a carbohydrate-binding module of family 14 (CBM14) to bind chitin in fungal cell walls and protect them from host chitinases during infection. Here, we show that gene duplication in the Avr4 family produced an Avr4-2 paralog with a previously unknown effector function. Specifically, we functionally characterize PfAvr4-2, a paralog of PfAvr4 in the tomato pathogen Pseudocercospora fuligena, and show that although it contains a CBM14 domain, it does not bind chitin or protect fungi against chitinases. Instead, PfAvr4-2 interacts with highly de-esterified pectin in the plant's middle lamellae or primary cell walls and interferes with Ca2+-mediated cross-linking at cell-cell junction zones, thus loosening the plant cell wall structure and synergizing the activity of pathogen secreted endo-polygalacturonases.Hydrogels consist of a cross-linked porous polymer network and water molecules occupying the interspace between the polymer chains. Therefore, hydrogels are soft and moisturized, with mechanical structures and physical properties similar to those of human tissue. Such hydrogels have a potential to turn the microscale gap between wearable devices and human skin into a tissue-like space. Here, we present material and device strategies to form a tissue-like, quasi-solid interface between wearable bioelectronics and human skin. The key material is an ultrathin type of functionalized hydrogel that shows unusual features of high mass-permeability and low impedance. The functionalized hydrogel acted as a liquid electrolyte on the skin and formed an extremely conformal and low-impedance interface for wearable electrochemical biosensors and electrical stimulators. Furthermore, its porous structure and ultrathin thickness facilitated the efficient transport of target molecules through the interface. Therefore, this functionalized hydrogel can maximize the performance of various wearable bioelectronics.Molecular descriptors are essential to not only quantitative structure-activity relationship (QSAR) models but also machine learning-based material, chemical, and biological data analysis. Here, we propose persistent spectral-based machine learning (PerSpect ML) models for drug design. Different from all previous spectral models, a filtration process is introduced to generate a sequence of spectral models at various different scales. PerSpect attributes are defined as the function of spectral variables over the filtration value. Molecular descriptors obtained from PerSpect attributes are combined with machine learning models for protein-ligand binding affinity prediction. Our results, for the three most commonly used databases including PDBbind-2007, PDBbind-2013, and PDBbind-2016, are better than all existing models, as far as we know. The proposed PerSpect theory provides a powerful feature engineering framework. PerSpect ML models demonstrate great potential to significantly improve the performance of learning models in molecular data analysis.Molecular segregation and biopolymer manipulation require the action of molecular motors to do work by applying directional forces to macromolecules. The additional strand conserved E (ASCE) ring motors are an ancient family of molecular motors responsible for diverse biological polymer manipulation tasks. Viruses use ASCE segregation motors to package their genomes into their protein capsids and provide accessible experimental systems due to their relative simplicity. We show by cryo-EM-focused image reconstruction that ASCE ATPases in viral double-stranded DNA (dsDNA) packaging motors adopt helical symmetry complementary to their dsDNA substrates. Together with previous data, our results suggest that these motors cycle between helical and planar configurations, providing a possible mechanism for directional translocation of DNA. Similar changes in quaternary structure have been observed for proteasome and helicase motors, suggesting an ancient and common mechanism of force generation that has been adapted for specific tasks over the course of evolution.Pure organic persistent room temperature phosphorescence (RTP) has shown great potential in information encryption, optoelectronic devices, and bio-applications. However, trace impurities are generated in synthesis, causing unpredictable effects on the luminescence properties. Here, an impurity is isolated from a pure organic RTP system and structurally characterized that caused an unusual ultralong RTP in matrix even at 0.01 mole percent content. Inspired by this effect, a series of compounds are screened out to form the bicomponent RTP system by the trace ingredient incorporation method. The RTP quantum yields reach as high as 74.2%, and the lifetimes reach up to 430 ms. Flexible application of trace ingredients to construct RTP materials has become an eye-catching strategy with high efficiency, economy, and potential for applications as well as easy preparation.Angkor is one of the world's largest premodern settlement complexes (9th to 15th centuries CE), but to date, no comprehensive demographic study has been completed, and key aspects of its population and demographic history remain unknown. Here, we combine lidar, archaeological excavation data, radiocarbon dates, and machine learning algorithms to create maps that model the development of the city and its population growth through time. We conclude that the Greater Angkor Region was home to approximately 700,000 to 900,000 inhabitants at its apogee in the 13th century CE. This granular, diachronic, paleodemographic model of the Angkor complex can be applied to any ancient civilization.There is an urgent need to identify vulnerabilities in pancreatic ductal adenocarcinoma (PDAC). PDAC cells acquire metabolic changes that augment NADPH production and cytosolic redox homeostasis. Here, we show that high NADPH levels drive activity of NADPH oxidase 4 (NOX4) expressed in the endoplasmic reticulum (ER) membrane. NOX4 produces H2O2 metabolized by peroxiredoxin 4 (PRDX4) in the ER lumen. Using functional genomics and subsequent in vitro and in vivo validations, we find that PDAC cell lines with high NADPH levels are dependent on PRDX4 for their growth and survival. PRDX4 addiction is associated with increased reactive oxygen species, a DNA-PKcs-governed DNA damage response and radiosensitivity, which can be rescued by depletion of NOX4 or NADPH. Hence, this study has identified NOX4 as a protein that paradoxically converts the reducing power of the cytosol to an ER-specific oxidative stress vulnerability in PDAC that may be therapeutically exploited by targeting PRDX4.Realizing nonlinear interactions between spatially separated particles can advance molecular science and technology, including remote catalysis of chemical reactions, ultrafast processing of information in infrared (IR) photonic circuitry, and advanced platforms for quantum simulations with increased complexity. Here, we achieved nonlinear interactions at ultrafast time scale between polaritons contained in spatially adjacent cavities in the mid-IR regime, altering polaritons in one cavity by pumping polaritons in an adjacent one. This was done by strong coupling molecular vibrational modes with photon modes, a process that combines characteristics of both photon delocalization and molecular nonlinearity. The dual photon/molecule character of polaritons enables delocalized nonlinearity-a property that neither molecular nor cavity mode would have alone.There has been increasing interest in wireless, miniaturized implantable medical devices for in vivo and in situ physiological monitoring. Here, we present such an implant that uses a conventional ultrasound imager for wireless powering and data communication and acts as a probe for real-time temperature sensing, including the monitoring of body temperature and temperature changes resulting from therapeutic application of ultrasound. The sub-0.1-mm3, sub-1-nW device, referred to as a mote, achieves aggressive miniaturization through the monolithic integration of a custom low-power temperature sensor chip with a microscale piezoelectric transducer fabricated on top of the chip. The small displaced volume of these motes allows them to be implanted or injected using minimally invasive techniques with improved biocompatibility. We demonstrate their sensing functionality in vivo for an ultrasound neurostimulation procedure in mice. Our motes have the potential to be adapted to the distributed and localized sensing of other clinically relevant physiological parameters.In the fractional quantum Hall effect, the elementary excitations are quasi-particles with fractional charges as predicted by theory and demonstrated by noise and interference experiments. We observe Coulomb blockade of fractional charges in the measured magneto-conductance of a 1.4-micron-wide quantum dot. Interaction-driven edge reconstruction separates the dot into concentric compressible regions with fractionally charged excitations and incompressible regions acting as tunnel barriers for quasi-particles. Our data show the formation of incompressible regions of filling factors 2/3 and 1/3. Epacadostat concentration Comparing data at fractional filling factors to filling factor 2, we extract the fractional quasi-particle charge e */e = 0.32 ± 0.03 and 0.35 ± 0.05. Our investigations extend and complement quantum Hall Fabry-Pérot interference experiments investigating the nature of anyonic fractional quasi-particles.Elevated ambient temperature has wide effects on plant growth and development. ELF3, a proposed thermosensor, negatively regulates protein activity of the growth-promoting factor PIF4, and such an inhibitory effect is subjected to attenuation at warm temperature. However, how ELF3 stability is regulated at warm temperature remains enigmatic. Here, we report the identification of XBAT31 as the E3 ligase that mediates ELF3 degradation in response to warm temperature in Arabidopsis XBAT31 interacts with ELF3, ubiquitinates ELF3, and promotes ELF3 degradation via the 26S proteasome. Mutation of XBAT31 results in enhanced accumulation of ELF3 and reduced hypocotyl elongation at warm temperature. In contrast, overexpression of XBAT31 accelerates ELF3 degradation and promotes hypocotyl growth. Furthermore, XBAT31 interacts with the B-box protein BBX18, and the XBAT31-mediated ELF3 degradation is dependent on BBX18 Thus, our findings reveal that XBAT31-mediated destruction of ELF3 represents an additional regulatory layer of complexity in temperature signaling during plant thermomorphogenesis.