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Metabolome profiling dissects the oat (Avena sativa L.) innate immune response to Pseudomonas syringae pathovars
One of the most important characteristics of successful plant defence is the ability to rapidly identify potential threats in the surrounding environment. Plants rely on the perception of microbe-derived molecular pattern chemicals for this recognition, which initiates a number of induced defence reactions that ultimately increase plant resistance. The metabolome acts as a metabolic fingerprint of the biochemical activities of a biological system under particular conditions, and therefore provides a functional readout of the cellular mechanisms involved. Untargeted metabolomics was applied to decipher the biochemical processes related to defence responses of oat plants inoculated with pathovars of Pseudomonas syringae (pathogenic and non-pathogenic on oat) and thereby identify signatory markers that are involved in host or nonhost defence responses. The strains were P. syringae pv. coronafaciens (Ps-c), P. syringae pv. tabaci, P. syringae pv. tomato DC3000 and the hrcC mutant of DC3000. At the seedling growth stage, metabolic alterations in the Dunnart oat cultivar (tolerant to Ps-c) in response to inoculation with the respective P. syringae pathovars were examined following perception and response assays. Following inoculation, plants were monitored for symptom development and harvested at 2-, 4- and 6 d.p.i. Methanolic leaf extracts were analysed by ultra-high-performance liquid chromatography (UHPLC) connected to high-definition mass spectrometry. Chemometric modelling and multivariate statistical analysis indicated time-related metabolic reconfigurations that point to host and nonhost interactions in response to bacterial inoculation/infection. Metabolic profiles derived from further multivariate data analyses revealed a range of metabolite classes involved in the respective defence responses, including fatty acids, amino acids, phenolic acids and phenolic amides, flavonoids, saponins, and alkaloids. The findings in this study allowed the elucidation of metabolic changes involved in oat defence responses to a range of pathovars of P. syringae and ultimately contribute to a more comprehensive view of the oat plant metabolism under biotic stress during host vs nonhost interactions.
Seasonal spatial-temporal trends of vegetation recovery in burned areas across Africa
Africa is entering a new fire paradigm, with climate change and increasing anthropogenic pressure shifting the patterns of frequency and severity. Thus, it is crucial to use available information and technologies to understand vegetation dynamics during the post-fire recovery processes. The main objective of this study was to evaluate the seasonal spatio-temporal trends of vegetation recovery in response to fires across Africa, from 2001 to 2020. Non-parametric tests were used to analyze MODIS Normalized Difference Vegetation Index (NDVI) products comparing the following three-month seasonal periods: December-February (DJF), March-May (MAM), June-August (JJA), and September-November (SON). We evaluated the seasonal spatial trends of NDVI in burned areas by hemisphere, territory, or country, and by land cover types, and fire recurrences, with a focus on forested areas. The relationships between the seasonal spatial trend and three climatic variables (i.e. maximum air temperature, precipitation, and vapor pressure deficit) were then analyzed. For the 8.7 million km2 burned in Africa over the past 22 years, we observed several seasonal spatial trends of NDVI. The highest proportions of areas with increasing trend (p < 0.05) was recorded in MAM for both hemispheres, with 22.0% in the Northern Hemisphere and 17.4% in the Southern Hemisphere. In contrast, areas with decreasing trends (p < 0.05), showed 4.8–5.5% of burned area in the Northern Hemisphere, peaking in JJA, while the Southern Hemisphere showed a range of 7.1 to 10.9% with the highest proportion also in JJA. Regarding land cover types, 48.0% of fires occurred in forests, 24.1% in shrublands, 16.6% in agricultural fields, and 8.9% in grasslands/savannas. Consistent with the overall trend, the area exhibiting an increasing trend in NDVI values (p < 0.05) within forested regions had the highest proportion in MAM, with 19.9% in the Northern Hemisphere and 20.6% in the Southern Hemisphere. Conversely, the largest decreasing trend (p < 0.05) was observed in DJF in the Northern Hemisphere (2.7–2.9%) and in JJA in the Southern Hemisphere (7.2–10.4%). Seasonally, we found a high variability of regeneration trends of forested areas based on fire recurrences. In addition, we found that of the three climatic variables, increasing vapor pressure deficit values were more related to decreasing NDVI levels. These results indicate a strong component of seasonality with respect to fires, trends of vegetation increase or decrease in the different vegetation covers of the African continent, and they contribute to the understanding of climatic conditions that contribute to vegetation recovery. This information is helpful for researchers and decision makers to act on specific sites during restoration processes.
Impact of health education on knowledge retention among caregivers of hypertensive patients: A prospective cross-sectional study in rural Malawi
Hypertension is a widespread and life-threatening condition affecting one-third of adults globally. In low- and middle-income countries, like Malawi, the burden of hypertension is escalating due to inadequate healthcare resources and lifestyle changes. Family members often become primary caregivers, playing a crucial role in managing hypertension through support and adherence to treatment. This study examined caregivers’ knowledge retention by evaluating their pre- and post-health education knowledge levels. This was a prospective cross-sectional study in Neno, Malawi, a rural setting. 422 caregivers were enrolled from the Integrated Chronic Care Clinic (IC3). A structured questionnaire was used to collect baseline, post-health education, and week six data. Using SPSS V 22.0, comparison of knowledge, attitude, and practices (KAP) scores, correlation between KAP and between KAP and social demographic characteristics were done using Wilcoxon signed-rank test, Pearson correlation, and independent t-test respectively. Among the 422 caregivers who participated in the study, 267 (63.2%) were females and mean age was 44.94 years. The baseline mean knowledge level score was 9.5 (38.0%) and rose to 21.08 (84.3%) p = 0.000 immediate post-health education and a 2.1% decrease 20.54 (82.2%) p<0.001 at week six from the immediate post health education score. Attitude improved from 16.76 (93.1%) at baseline to 17.74 (98.6%) at the six-week mark. Similarly, the mean practice score rose from 25.24 (78.9%) at baseline to 27.42 (85.7%) at week six. There was a positive correlation between KAP while age had a negative correlation with knowledge (r = -0.146; p = 0.003). There was a significant difference between different education levels on knowledge retention p = 0.009. There was a positive and good knowledge retention among caregivers of hypertensive patients after health education at the week six mark. With improved knowledge and the ability to retain it resulting in improved attitude and practices, caregivers are a cornerstone for continued and improved hypertension care for the patients.
Physiotherapy under pressure: A cross-sectional study on the interplay between perfectionism, moral injury, and burnout
Background Given the escalating challenges for UK-based physiotherapists in workload pressures, budget constraints, staff shortages and patient wait times, the profession (of 65,000 registered physiotherapists) necessitates immediate attention to the health and well-being of the therapists. This pioneering study aims to examine perfectionism, moral injury, and burnout among UK-based physiotherapists across the NHS, private practice, sports, and academia. Method This cross-sectional study utilised an online survey and implementation of Structure Equation Modelling (SEM) to assess the interplay of perfectionism (Multidimensional Perfectionism Scale-Short Form), moral injury (Moral Injury Symptoms Scale-Healthcare Professionals), and burnout (Shirom-Melamed Burnout Questionnaire). Our sample size calculation represents the UK physiotherapy profession, utilising a 95% confidence interval with a 5% margin of error. Findings Our analysis conducted on (n = 402) UK-based physiotherapists reveals significant burnout levels, with 96% of participants presenting with moderate to high burnout scores. SEM revealed perfectionism and moral injury collectively accounted for a substantial 62% of burnout variability, highlighting their sequential impact on burnout manifestation. Interpretation With such high levels of burnout, urgent intervention is paramount. Elevated burnout presents challenges for the physiotherapy profession as staff retention, accurate and effective patient care, and overall health are severely impacted due to burnout. Recognising and addressing perfectionism and moral injury, such as through amendment or development of policy, becomes pivotal to mitigate its impact on individual and collective health.
Simulation research on dynamic characteristics of scroll compressor with flexible clearance
The scroll compressor is a rotating machinery with high-speed and high-precision characteristics. In this paper, a vector model of the kinematic pair was constructed based on two-state clearance. To confirm the adverse effects of tiny clearance (0<r≤0.1mm) on the scroll compressor, a dynamics simulation of the spindle was performed under flexible contact conditions with different clearances. The study indicates that simulation results for flexible and rigid bodies are vastly different, and the former is closer to reality. Compared with the case in an ideal state (0mm), clearance at 0.01mm and 0.04mm can cause an enormous impact on the critical bearing components of the spindle, such as the orbiting scroll, cross-slip ring, and support bearing, which results in unexpected vibration and noise. However, when the clearance increases to 0.07mm and 0.1mm, the collision amplitude and friction resistance inside the needle bearing are relatively small, which avoids violent impacts on the machine. This paper considers the effect of spindle flexibility and transmission clearance simultaneously, which helps to explore the running mechanism of a scroll compressor with clearance.
A ribosome-associating chaperone mediates GTP-driven vectorial folding of nascent eEF1A
A minimal gene set characterizes TIL specific for diverse tumor antigens across different cancer types
Abstract Identifying tumor-specific T cell clones that mediate immunotherapy responses remains challenging. Mutation-associated neoantigen (MANA) -specific CD8+ tumor-infiltrating lymphocytes (TIL) have been shown to express high levels of CXCL13 and CD39 (ENTPD1), and low IL-7 receptor (IL7R) levels in many cancer types, but their collective relevance to T cell functionality has not been established. Here we present an integrative tool to identify MANA-specific TIL using weighted expression levels of these three genes in lung cancer and melanoma single-cell RNAseq datasets. Our three-gene “MANAscore” algorithm outperforms other RNAseq-based algorithms in identifying validated neoantigen-specific CD8+ clones, and accurately identifies TILs that recognize other classes of tumor antigens, including cancer testis antigens, endogenous retroviruses and viral oncogenes. Most of these TIL are characterized by a tissue resident memory gene expression program. Putative tumor-reactive cells (pTRC) identified via MANAscore in anti-PD-1-treated lung tumors had higher expression of checkpoint and cytotoxicity-related genes relative to putative non-tumor-reactive cells. pTRC in pathologically responding tumors showed distinguished gene expression patterns and trajectories. Collectively, we show that MANAscore is a robust tool that can greatly enrich candidate tumor-specific T cells and be used to understand the functional programming of tumor-reactive TIL.
Divergent alkynylative difunctionalization of amide bonds through C–O deoxygenation versus C–N deamination
A novel early stage drip irrigation system cost estimation model based on management and environmental variables
Thiophene-fused aromatic belts
Intelligent deep federated learning model for enhancing security in internet of things enabled edge computing environment
Stimulus-activated ribonuclease targeting chimeras for tumor microenvironment activated cancer therapy
Fugacity-based multimedia transport modeling and risk assessment of PAHs in Urumqi
Unlocking the potential of hydrogen deuterium exchange via an iterative continuous-flow deuteration process
Self-control moderates the impacts of physical activity on the sleep quality of university students
The assembly factor Reh1 is released from the ribosome during its initial round of translation
Object identity representation occurs early in the archerfish visual system
Early tolerance and late persistence as alternative drug responses in cancer
Research on cutting mechanism and process optimization method of gear skiving
Abstract The cutting force and cutting temperature have a significant impact on the service life and durability of gear skiving cutters. Due to unreasonable design, the existing process parameters lead to dramatically nonuniform cutting force and cutting temperature, which aggravates the rapid wear of gear skiving cutters. To address this issue, this paper first establishes a finite element model of skiving the internal circular arc tooth in pin wheel housing, and the simulation model is simplified to improve computation efficiency. Next, the impact of single process parameter on cutting force and cutting temperature is analyzed by controlling variable. Then, an orthogonal experiment is designed and the method of range analysis is employed to evaluate the significance of each process parameter. Furthermore, a prediction model of cutting force and cutting temperature is established using a neural network optimized by genetic algorithm. This prediction model allows for the construction of a multi-objective optimization model for the process parameters. By solving this model, the optimal combination of process parameters within the given ranges can be obtained to achieve reasonable and balanced cutting force and cutting temperature.