Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15N-Stable Isotope Labeling and ProteinTurnover Algorithm.

Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for the cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15N-stable isotope labeling and ultra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22 °C and 30 °C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adaptations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mitochondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis highlights the intricate balance between proteome stability and adaptability, advancing our understanding of plant responses to heat stress and supporting the development of improved thermotolerant crops.

Predicting prognosis in patients with stroke treated with intravenous alteplase through blood pressure changes: A machine learning-based approach.

The use of machine learning (ML) in predicting disease prognosis has increased, and researchers have adopted different methods for variable selection to optimize early screening for AIS to determine its prognosis as soon as possible. We aimed to improve the understanding of the predictors of poor functional outcome at three months after discharge in AIS patients treated with intravenous thrombolysis and to construct a highly effective prognostic model to improve prediction accuracy. And four ML methods (random forest, support vector machine, naive Bayesian, and logistic regression) were used to screen and recombine the features for construction of an ML prognostic model. A total of 352 patients that had experienced AIS and had been treated with intravenous thrombolysis were recruited. The variables included in the model were NIHSS on admission, age, white blood cell count, percentage of neutrophils and triglyceride after thrombolysis, tirofiban, early neurological deterioration, early neurological improvement, and BP at each time point or period. The model's area under the curve for predicting 30-day modified Rankin scale was 0.790 with random forest, 0.542 with support vector machine, 0.411 with naive Bayesian, and 0.661 with logistic regression. The random forest model was shown to accurately evaluate the prognosis of AIS patients treated with intravenous thrombolysis, and therefore they may be helpful for accurate and personalized secondary prevention. The model offers improved prediction accuracy that may reduce rates of misdiagnosis and missed diagnosis in patients with AIS.

Effectiveness and safety of early postpyloric feeding during therapeutic hypothermia in patients with large hemispheric infarction: A retrospective cohort study.

BACKGROUND: What kind of feeding should be provided during therapeutic hypothermia (TH) in patients with large hemispheric infarction (LHI) is not clear. Therefore, we conducted a retrospective observational study to determine whether providing early postpyloric feeding (PPF) (<24 h after admission) is beneficial or harmful for patients with this condition. METHODS: This study retrospectively screened 78 patients with LHI who were treated with TH from one neurological intensive care unit (ICU). The patients were receiving either early PPF (n = 52) or early parenteral nutrition (PN) (n = 26). Data regarding 30-day mortality, neurological outcome, nutrition-related laboratory indicators, ICU hospitalization time, mechanical ventilation (MV) duration, and complications were collected. RESULTS: A greater number of patients who received early PPF had favorable neurologic outcome than those who received early PN (57.7% vs 30.7%, P = 0.025). The early PPF group had a lower severity of pulmonary infection than the early PN group, as measured by the Clinical Pulmonary Infection Score (7.33 ± 0.96 vs 9.42 ± 2.11, P = 0.006). The total protein and hemoglobin levels in the early PPF group were higher than those in the early PN group (59.56 ± 5.09 vs 56.52 ± 7.94 g/L, P = 0.046; 131.06 ± 19.58 vs 122.07 ± 17.72 g/L, P = 0.045). The MV duration and ICU hospitalization time were shorter in the early PPF group (13 [9;21] vs 21 [14;30] days, P = 0.006; 28 [22;36] vs 34 [33;51] days, P = 0.014). There were no significant differences in the incidence of catheter-related bloodstream infections, 30-day mortality, or nutrition intolerance between the two groups. CONCLUSION: Early PPF is an effective and safe enteral nutrition method for patients with LHI receiving TH.

Mass spectrometry in the discovery of peptides involved in intercellular communication: From targeted to untargeted peptidomics approaches.

Endogenous peptide hormones represent an essential class of biomolecules, which regulate cell-cell communications in diverse physiological processes of organisms. Mass spectrometry (MS) has been developed to be a powerful technology for identifying and quantifying peptides in a highly efficient manner. However, it is difficult to directly identify these peptide hormones due to their diverse characteristics, dynamic regulations, low abundance, and existence in a complicated biological matrix. Here, we summarize and discuss the roles of targeted and untargeted MS in discovering peptide hormones using bioassay-guided purification, bioinformatics screening, or the peptidomics-based approach. Although the peptidomics approach is expected to discover novel peptide hormones unbiasedly, only a limited number of successful cases have been reported. The critical challenges and corresponding measures for peptidomics from the steps of sample preparation, peptide extraction, and separation to the MS data acquisition and analysis are also discussed. We also identify emerging technologies and methods that can be integrated into the discovery platform toward the comprehensive study of endogenous peptide hormones.

Factors That Influence Compliance to Long-Term Remote Ischemic Conditioning Treatment in Patients With Ischemic Stroke.

Objectives: To investigate the treatment compliance of patients with ischemic stroke to remote ischemic conditioning (RIC) and to determine the factors that influence compliance. Methods: We conducted a retrospective study of patients with ischemic stroke who were treated with RIC. Treatment compliance was determined and analyzed in patients who had received 1 year of RIC training. Factors that influenced patient compliance were also determined using univariate and multivariate regression analyses. Results: Between March 2017 and February 2018, 91 patients were recruited into this study. The mean (±SD) age was 57.98 ± 10.76 years, and 78 (85.7%) patients were male. The baseline Kolcaba comfort scale of patients with good compliance scores were higher than those with poor compliance. The scores of the four dimensions in the scale and the total score are as follows: physiological dimensions, 15.0 (12.0,17.0) vs 17.0 (13.0,19.0); psychological dimensions, 30.0 (25.0,34.0) vs 31.0 (27.0,35.0); sociological dimensions, 20.0 (18.0,24.0) vs 21.0 (18.0,23.0); environmental dimensions, 19.0 (12.0,24.0) vs 20.0 (17.0,22.0); and total points, 82.0 (69.0,94.0) vs 91.0 (78.0,98.0). the differences between the groups were significant (p < 0.05), except for the sociological dimensions. A history of hypertension, number of follow-ups, and the physiological, psychological, and environmental dimensions of the comfort scale were related to patient compliance, out of which the number of follow-ups (Adjusted OR = 2.498, 95% confidence interval (CI) 1.257-4.964) and the physiological discomfort (Adjusted OR = 1.128, 95% CI 1.029-1.236) independently influenced compliance (p < 0.05). Conclusion: In patients with ischemic cerebrovascular disease who were treated with RIC, the number of follow-up visits and physiological discomfort associated with RIC treatment independently influenced patient compliance. Further studies are needed to investigate the RIC protocols and their corresponding nursing models.

Predicting prognosis in patients with stroke treated with intravenous alteplase through the 24-h trajectory of blood pressure changes.

Blood pressure (BP) monitored within 24 h from the beginning of intravenous thrombolysis (IVT) with alteplase, is one of the important factors affecting the prognosis of patients with acute ischemic stroke (AIS). This study aimed to explore longitudinal BP trajectory patterns and determine their association with stroke prognosis after thrombolysis. From November 2018 to September 2019, a total of 391 patients were enrolled consecutively during the study period, and 353 patients were ultimately analyzed. Five systolic (SBP) and four diastolic blood pressure (DBP) trajectory subgroups were identified. The regression analysis showed that when compared with the rapidly moderate stable group, the continuous fluctuation-very high level SBP group (odds ratio [OR]: 2.743, 95% confidence interval [CI]: 1.008-7.467) was associated with early neurological deterioration (END). Both the rapid drop-high level SBP (OR: 0.448, 95% CI: 0.219-0.919) and DBP groups (OR: 0.399, 95% CI: 0.219-0.727) were associated with early neurological improvement (ENI). Moreover, there was a U-shaped correlation between the OR value of SBP trajectory group and favorable outcome (the modified Rankin Scale [mRS] score 0-2) at 3 months: the slow drop-low level SBP group represent a well-established unfavorable outcome risk factor (OR:5.239, 95% CI: 1.271-21.595), and extremely high SBP-the continuous fluctuation-very high level SBP group, are equally associated with elevated unfavorable outcome risk (OR:3.797, 95% CI: 1.486-9.697). The continuous fluctuation-very high level DBP group was statistically significant in mRS (OR: 3.387, CI: 1.185-9.683). The BP trajectory groups show varying clinical features and risk of neurological dysfunction. The findings may help identify potential candidates for clinical BP monitoring, control, and specialized care.

Quantitative Proteomics Reveals the Dynamic Regulation of the Tomato Proteome in Response to Phytophthora infestans.

Late blight (LB) disease is a major threat to potato and tomato production. It is caused by the hemibiotrophic pathogen, Phytophthora infestans. P. infestans can destroy all of the major organs in plants of susceptible crops and result in a total loss of productivity. At the early pathogenesis stage, this hemibiotrophic oomycete pathogen causes an asymptomatic biotrophic infection in hosts, which then progresses to a necrotrophic phase at the later infection stage. In this study, to examine how the tomato proteome is regulated by P. infestans at different stages of pathogenesis, a data-independent acquisition (DIA) proteomics approach was used to trace the dynamics of the protein regulation. A comprehensive picture of the regulation of tomato proteins functioning in the immunity, signaling, defense, and metabolism pathways at different stages of P. infestans infection is revealed. Among the regulated proteins, several involved in mediating plant defense responses were found to be differentially regulated at the transcriptional or translational levels across different pathogenesis phases. This study increases understanding of the pathogenesis of P. infestans in tomato and also identifies key transcriptional and translational events possibly targeted by the pathogen during different phases of its life cycle, thus providing novel insights for developing a new strategy towards better control of LB disease in tomato.

The role of peptides cleaved from protein precursors in eliciting plant stress reactions.

As sessile organisms, plants are exposed to diverse abiotic and biotic stresses, and thus have developed complex signaling mechanisms that orchestrate multiple stress responses. Plant peptides have recently emerged as key signaling molecules of stress responses, not only to mechanical wounding and pathogen infection but also to nutrient imbalance, drought and high salinity. The currently identified stress-related signaling peptides in plants are derived from proteolytic processing of protein precursors. Here, we review these protein-derived peptides and the evidence for their functions in stress signaling. We recommend potential research directions that could clarify their roles in stress biology, and propose possible crosstalk with regard to the physiological outcome. The stress-centric perspective allows us to highlight the crucial roles of peptides in regulating the dynamics of stress physiology. Inspired by historic and recent findings, we review how peptides initiate complex molecular interactions to coordinate biotic and abiotic stress responses in plants.

Application of Data-Independent Acquisition Approach to Study the Proteome Change from Early to Later Phases of Tomato Pathogenesis Responses.

Plants and pathogens are entangled in a continual arms race. Plants have evolved dynamic defence and immune mechanisms to resist infection and enhance immunity for second wave attacks from the same or different types of pathogenic species. In addition to evolutionarily and physiological changes, plant-pathogen interaction is also highly dynamic at the molecular level. Recently, an emerging quantitative mass spectrometry-based proteomics approach named data-independent acquisition (DIA), has been developed for the analysis of the proteome in a high-throughput fashion. In this study, the DIA approach was applied to quantitatively trace the change in the plant proteome from the early to the later stage of pathogenesis progression. This study revealed that at the early stage of the pathogenesis response, proteins directly related to the chaperon were regulated for the defence proteins. At the later stage, not only the defence proteins but also a set of the pathogen-associated molecular pattern-triggered immunity (PTI) and effector triggered immunity (ETI)-related proteins were highly induced. Our findings show the dynamics of the plant regulation of pathogenesis at the protein level and demonstrate the potential of using the DIA approach for tracing the dynamics of the plant proteome during pathogenesis responses.

Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants.

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

Arabidopsis IAR4 modulates auxin response by regulating auxin homeostasis.

In a screen for enhancers of tir1-1 auxin resistance, we identified two novel alleles of the putative mitochondrial pyruvate dehydrogenase E1alpha-subunit, IAA-Alanine Resistant4 (IAR4). In addition to enhancing the auxin response defects of tir1-1, iar4 single mutants exhibit numerous auxin-related phenotypes including auxin-resistant root growth and reduced lateral root development, as well as defects in primary root growth, root hair initiation, and root hair elongation. Remarkably, all of these iar4 mutant phenotypes were rescued when endogenous indole-3-acetic acid (IAA) levels were increased by growth at high temperature or overexpression of the YUCCA1 IAA biosynthetic enzyme, suggesting that iar4 mutations may alter IAA homeostasis rather than auxin response. Consistent with this possibility, iar4 mutants exhibit increased Aux/IAA stability compared to wild type under basal conditions, but not in response to an auxin treatment. Measurements of free IAA levels detected no significant difference between iar4-3 and wild-type controls. However, we consistently observed significantly higher levels of IAA-amino acid conjugates in the iar4-3 mutant. Furthermore, using stable isotope-labeled IAA precursors, we observed a significant increase in the relative utilization of the Trp-independent IAA biosynthetic pathway in iar4-3. We therefore suggest that the auxin phenotypes of iar4 mutants are the result of altered IAA homeostasis.