Zhaobass3317

Overall, our results suggest that tissue-to-tissue specific levels of selected near-cognate tRNAs may have a vital potential to fine-tune the final landscape of the human proteome, as well as that of its viral pathogens.High-temperature is the most limiting factor in the growth of cool-season turfgrass. To cope with high-temperature stress, grass often adopt a memory response by remembering one past recurring stress and preparing a quicker and more robust reaction to the next stress exposure. However, little is known about how stress memory genes regulate the thermomemory response in cool-season turfgrass. Here, we characterized a transcriptional memory gene, Fa-heat shock protein 17.8 Class II (FaHSP17.8-CII) in a cool-season turfgrass species, tall fescue (Festuca arundinacea Schreb.). The thermomemory of FaHSP17.8-CII continued for more than four days and was associated with a high H3K4me3 level in tall fescue under heat stress (HS). Furthermore, heat acclimation or priming (ACC)-induced reactive oxygen species (ROS) accumulation and photosystem II (PSII) electron transport were memorable, and this memory response was controlled by FaHSP17.8-CII. In the fahsp17.8-CII mutant generated using CRISPR/Cas9, ACC+HS did not substantially block the ROS accumulation, the degeneration of chloroplast ultra-structure and the inhibition of PSII activity compared to HS alone. However, overexpression of FaHSP17.8-CII in tall fescue reduced ROS accumulation and chloroplast ultra-structure damage, and improved chlorophyll content and PSII activity under ACC+HS compared with that HS alone. These findings unveil a FaHSP17.8-CII-PSII-ROS module regulating transcriptional memory to enhance thermotolerance in cool-season turfgrass.Base-modification can occur throughout a transfer RNA molecule; however, elaboration is particularly prevalent at position 34 of the anticodon loop (the wobble position), where it functions to influence protein translation. Previously, we demonstrated that the queuosine modification at position 34 can be substituted with an artificial analogue via the queuine tRNA ribosyltransferase enzyme to induce disease recovery in an animal model of multiple sclerosis. Here, we demonstrate that the human enzyme can recognize a very broad range of artificial 7-deazaguanine derivatives for transfer RNA incorporation. By contrast, the enzyme displays strict specificity for transfer RNA species decoding the dual synonymous NAU/C codons, determined using a novel enzyme-RNA capture-release method. Our data highlight the broad scope and therapeutic potential of exploiting the queuosine incorporation pathway to intentionally engineer chemical diversity into the transfer RNA anticodon.

Health insurance coverage is associated with improved outcomes in patients with cancer. However, it is unknown whether Medicaid expansion through the Patient Protection and Affordable Care Act (ACA) was associated with improvements in the diagnosis and treatment of patients with genitourinary cancer.

To assess the association of Medicaid expansion with health insurance status, stage at diagnosis, and receipt of treatment among nonelderly patients with newly diagnosed kidney, bladder, or prostate cancer.

This case-control study included adults aged 18 to 64 years with a new primary diagnosis of kidney, bladder, or prostate cancer, selected from the National Cancer Database from January 1, 2011, to December 31, 2016. Patients in states that expanded Medicaid were the case group, and patients in nonexpansion states were the control group. Data were analyzed from January 2020 to March 2021.

State Medicaid expansion status.

Insurance status, stage at diagnosis, and receipt of cancer and stage-specific triding in low-income areas and reinforce the importance of improving access to care to all patients with cancer.

Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. learn more Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accuracy and consistency of wound area and PGT measurement, while improving efficiency of wound care workflows.

To develop a quantitative and qualitative method to evaluate AI-based wound assessment tools compared with expert human assessments.

This diagnostic study was performed across 2 independent wound centers using deidentified wound photographs collected for routine care (site 1, 110 photographs taken between May 1 and 31, 2018; site 2, 89 photographs taken between January 1 and December 31, 2019). Digital wound photographs of patients were selected chronologically from the electronic medical records from the general population of patients visiting the wound centers. For inclusion in the study, the complete wound edge and a ruler were required to be visible; circumferentwever, visual PGT estimates varied considerably (mean range, 34.8%; mean SD, 19.6%).

This study provides a framework for evaluating AI-based digital wound assessment tools that can be extended to automated measurements of other wound features or adapted to evaluate other AI-based digital image diagnostic tools. As AI-based wound assessment tools become more common across wound care settings, it will be important to rigorously validate their performance in helping clinicians obtain accurate wound assessments to guide clinical care.

This study provides a framework for evaluating AI-based digital wound assessment tools that can be extended to automated measurements of other wound features or adapted to evaluate other AI-based digital image diagnostic tools. As AI-based wound assessment tools become more common across wound care settings, it will be important to rigorously validate their performance in helping clinicians obtain accurate wound assessments to guide clinical care.

Curbing COVID-19 transmission is currently the greatest global public health challenge. Consumer digital tools used to collect data, such as the Apple-Google digital contact tracing program, offer opportunities to reduce COVID-19 transmission but introduce privacy concerns.

To assess uses of consumer digital information for COVID-19 control that US adults find acceptable and the factors associated with higher or lower approval of use of this information.

This cross-sectional survey study obtained data from a nationally representative sample of 6284 US adults recruited by email from the web-based Ipsos KnowledgePanel in July 2020. Respondents evaluated scenarios reflecting uses of digital data for COVID-19 control (case identification, digital contact tracing, policy setting, and enforcement of quarantines).

Levels of support for use of personal digital data in 9 scenarios to mitigate the spread of COVID-19 infection, rated on a Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Multivariable linear regression models were fitted for each scenario and included factors hypothesized to be associated with views about digital data use for COVID-19 mitigation measures.