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Lipochitooligosaccharide (LCO) perception by legumes is required to establish symbiotic relationships with nitrogen fixing bacteria. Here the authors show that nutrient starvation can activate LCO perception in cereals to promote symbiotic association with arbuscular mycorrhizal fungi.

Chloroplast development and brassinosteroid (BR) signaling both regulate plant photomorphogenesis. Here the authors show that DAY, a DnaJ-like domain-containing membrane protein, regulates both processes by binding and stabilizing both BRI1, the BR receptor, and POR, a key enzyme in chlorophyll biosynthesis.

Signaling via the D14L karrikin receptor conditions rice roots for association with arbuscular mycorrhizal fungi. Here, Choi et al. show that SMAX1, a rice homolog of an Arabidopsis repressor of karrikin signaling, acts downstream of D14L to suppress mycorrhizal symbiosis and strigolactone biosynthesis.

With the aim of providing holistic approaches to education, social and emotional learning (SEL) has gained significant attention within school systems across the world. SEL has been defined as the process through which individuals understand and regulate emotions, set and achieve positive goals, feel and show empathy towards others, establish and maintain positive relationships, and make responsible decisions. In an effort to integrate SEL into the academic domains of science, technology, engineering, arts, and math (STEAM) and to promote cross-cultural collaboration, three institutions came together to deliver a groundbreaking program for elementary school students from California and South Korea: the Global Summer Academy. The impact of SEL is even greater when students observe adults collaborating to establish a nurturing environment, modeling positive behaviors, and consistently promoting social and emotional concepts and skills. Thus, forming community partnerships across contexts and settings is an ideal strategy for enriching student learning and development. SEL activities such as mindfulness practice can aid students in regulating their emotions during STEAM tasks, enabling them to better reflect on and address their successes and failures. Such a reflective process not only improves student learning outcomes, but also facilitates the development of persistence, resilience, critical thinking, and growth mindset. Therefore, integrating SEL principles within STEAM activities not only enriches the academic experience, but also equips students with the social and emotional skills necessary for personal growth. To assess students' learning (i.e., what they learned, what they enjoyed, challenges they faced), brief interviews were conducted with all participants at the end of the week-long program. This feedback suggested four key themes -- problem solving, relationship skills, self-awareness, and emotion awareness.

Polysaccharide molecules chitooligosaccharides (COs) and peptidoglycan not only activate plant immunity but also trigger plant symbiosis signalling. Here the authors show that a combination of COs and lipochitooligosaccharides (LCOs) act synergistically to suppress immunity and promote symbiosis to facilitate beneficial fungal associations.

Cultivated barley (Hordeum vulgare L.) is one of the most produced cereal crops worldwide after maize, bread wheat, and rice. Barley is an important crop species not only as a food source, but also in plant genetics because it harbors numerous stress response alleles in its genome that can be exploited for crop engineering. However, the functional annotation of its genome is relatively poor compared with other major crops. Moreover, bioinformatics tools for system-wide analyses of omics data from barley are not yet available. We have thus developed BarleyNet, a co-functional network of 26,145 barley genes, along with a web server for network-based predictions (http://www.inetbio.org/barleynet). We demonstrated that BarleyNet's prediction of biological processes is more accurate than that of an existing barley gene network. We implemented three complementary network-based algorithms for prioritizing genes or functional concepts to study genetic components of complex traits such as environmental stress responses: (i) a pathway-centric search for candidate genes of pathways or complex traits; (ii) a gene-centric search to infer novel functional concepts for genes; and (iii) a context-centric search for novel genes associated with stress response. We demonstrated the usefulness of these network analysis tools in the study of stress response using proteomics and transcriptomics data from barley leaves and roots upon drought or heat stresses. These results suggest that BarleyNet will facilitate our understanding of the underlying genetic components of complex traits in barley.

Histone post-translational modifications (PTMs) create a powerful regulatory mechanism for maintaining chromosomal integrity in cells. Histone acetylation and methylation, the most widely studied histone PTMs, act in concert with chromatin-associated proteins to control access to genetic information during transcription. Alterations in cellular histone PTMs have been linked to disease states and have crucial biomarker and therapeutic potential. Traditional bottom-up mass spectrometry of histones requires large numbers of cells, typically one million or more. However, for some cell subtype-specific studies, it is difficult or impossible to obtain such large numbers of cells and quantification of rare histone PTMs is often unachievable. An established targeted LC-MS/MS method was used to quantify the abundance of histone PTMs from cell lines and primary human specimens. Sample preparation was modified by omitting nuclear isolation and reducing the rounds of histone derivatization to improve detection of histone peptides down to 1,000 cells. In the current study, we developed and validated a quantitative LC-MS/MS approach tailored for a targeted histone assay of 75 histone peptides with as few as 10,000 cells. Furthermore, we were able to detect and quantify 61 histone peptides from just 1,000 primary human stem cells. Detection of 37 histone peptides was possible from 1,000 acute myeloid leukemia patient cells. We anticipate that this revised method can be used in many applications where achieving large cell numbers is challenging, including rare human cell populations.

Recently, nanovaccine-based immunotherapy has been robustly investigated due to its potential in governing the immune response and generating long-term protective immunity. However, the presentation of a tumor peptide-major histocompatibility complex to T lymphocytes is still a challenge that needs to be addressed for eliciting potent antitumor immunity. Type 1 conventional dendritic cell (cDC1) subset is of particular interest due to its pivotal contribution in the cross-presentation of exogenous antigens to CD8+ T cells. Here, the DC-derived nanovaccine (denoted as Si9GM) selectively targets cDC1s with marginal loss of premature antigen release for effective stimulator of interferon genes (STING)-mediated antigen cross-presentation. Bone marrow dendritic cell (BMDC)-derived membranes, conjugated to cDC1-specific antibody (αCLEC9A) and binding to tumor peptide (OVA257-264), are coated onto dendrimer-like polyethylenimine (PEI)-grafted silica nanoparticles. Distinct molecular weight-cargos (αCLEC9A-OVA257-264 conjugates and 2′3′-cGAMP STING agonists) are loaded in hierarchical center-radial pores that enables lysosome escape for potent antigen-cross presentation and activates interferon type I, respectively. Impressively, Si9GM vaccination leads to the upregulation of cytotoxic T cells, a reduction in tumor regulatory T cells (Tregs), M1/M2 macrophage polarization, and immune response that synergizes with αPD-1 immune checkpoint blockade. This nanovaccine fulfills a dual role for both direct T cell activation as an artificial antigen-presenting cell and DC subset maturation, indicating its utility in clinical therapy and precision medicine.

Background: It is important to study differential inflammatory cellular migration, particularly of eosinophils and neutrophils, in asthma and how this is influenced by environmental stimuli such as allergen exposure and the effects of anti asthma therapy. Methods: We isolated blood neutrophils and eosinophils from 12 atopic asthmatic human volunteers (Group 1 — four Early Allergic Responders unchallenged (EAR); Group 2 — four Early and Late Allergic Responders (LAR) challenged; Group 3 — four EAR and LAR challenged and treated with systemic corticosteroids) using cGMP CD16 CliniMACS. Cells were isolated prior to allergen challenge where applicable, labelled with 99mTc-HMPAO and then re-infused intravenously. The kinetics of cellular influx/efflux into the lungs and other organs were imaged via scintigraphy over 4 h, starting at 5 to 6 h following allergen challenge where applicable. Results: Neutrophils and eosinophils were isolated to a mean (SD) purity of 98.36% (1.09) and 96.31% (3.0), respectively. Asthmatic neutrophils were activated at baseline, mean (SD) CD11bHigh cells 46 (10.50) %. Isolation and radiolabelling significantly increased their activation to >98%. Eosinophils were not activated at baseline, CD69+ cells 1.9 (0.6) %, increasing to 38 (3.46) % following isolation and labelling. Analysis of the kinetics of net eosinophil and neutrophil lung influx/efflux conformed to a net exponential clearance with respective mean half times of clearance 6.98 (2.18) and 14.01 (2.63) minutes for Group 1, 6.03 (0.72) and 16.04 (2.0) minutes for Group 2 and 5.63 (1.20) and 14.56 (3.36) minutes for Group 3. These did not significantly differ between the three asthma groups (p > 0.05). Conclusions: Isolation and radiolabelling significantly increased activation of eosinophils (CD69) and completely activated neutrophils (CD11bHigh) in all asthma groups. Net lung neutrophil efflux was significantly slower than that of eosinophils in all asthma study groups. There was a trend for pre-treatment with systemic corticosteroids to reduce lung retention of eosinophils following allergen challenge.

Abstract It is still challenging to predict the efficacy of cisplatin-based therapy, particularly in relation to the activation of macroautophagy/autophagy in oral squamous cell carcinoma (OSCC). We studied the effect of selected chromatin remodeling genes on the cisplatin resistance and their interplay with autophagy in 3-dimensional tumor model and xenografts. We analyzed gene expression patterns in the cisplatin-sensitive UMSCC1, and a paired cisplatin-resistant UM-Cis cells. Many histone protein gene clusters involved in nucleosome assembly showed significant difference of expression. Gain- and loss-of-function analyses revealed an inverse correlation between cisplatin resistance and HIST1H3D expression, while a positive correlation was observed with HIST3H2A or HIST3H2B expression. In UM-Cis, HIST3H2A- and HIST3H2B-mediated chromatin remodeling upregulates autophagy status, which results in cisplatin resistance. Additionally, knockdown of HIST3H2A or HIST3H2B downregulated autophagy-activating genes via chromatin compaction of their promoter regions. MiTF, one of the key autophagy regulators upregulated in UM-Cis, negatively regulated transcription of HIST1H3D, suggesting an interplay between chromatin remodeling-dependent cisplatin resistance and autophagy. On comparing the staining intensity between cisplatin-sensitive and –insensitive tissues from OSCC patients, protein expression pattern of the selected histone protein genes were matched with the in vitro data. By examining the relationship between autophagy and chromatin remodeling genes, we identified a set of candidate genes with potential use as markers predicting chemoresistance in OSCC biopsy samples.

The adverse effects of traffic-related air pollution on children's respiratory health have been widely reported, but few studies have evaluated the impact of traffic-control policies designed to reduce urban air pollution. We assessed associations between traffic-related air pollutants and respiratory/allergic symptoms amongst 8-9 year-old schoolchildren living within the London Low Emission Zone (LEZ). Information on respiratory/allergic symptoms was obtained using a parent-completed questionnaire and linked to modelled annual air pollutant concentrations based on the residential address of each child, using a multivariable mixed effects logistic regression analysis. Exposure to traffic-related air pollutants was associated with current rhinitis: NOx (OR 1.01, 95% CI 1.00-1.02), NO2 (1.03, 1.00-1.06), PM10 (1.16, 1.04-1.28) and PM2.5 (1.38, 1.08-1.78), all per μg/m3 of pollutant, but not with other respiratory/allergic symptoms. The LEZ did not reduce ambient air pollution levels, or affect the prevalence of respiratory/allergic symptoms over the period studied. These data confirm the previous association between traffic-related air pollutant exposures and symptoms of current rhinitis. Importantly, the London LEZ has not significantly improved air quality within the city, or the respiratory health of the resident population in its first three years of operation. This highlights the need for more robust measures to reduce traffic emissions.

Abstract The increasing use of sodium glucose transporter 2 inhibitors (SGLT2i) for treating cardiovascular (CV) diseases and type 2 diabetes (T2D) is accompanied by a rise in euglycemic diabetic ketoacidosis occurrences in cardiac surgery patients. Patients undergoing cardiac surgery, due to their pre-existing CV disease which often requires SGLT2i prescriptions, face an increased risk of postoperative metabolic acidosis (MA) or ketoacidosis (KA) associated with SGLT2i, compounded by fasting and surgical stress. The primary aim of this study is to quantify the incidence of SGLT2i-related postoperative MA or KA and to identify related risk factors. We analyzed data retrospectively of 823 cardiac surgery patients, including 46 treated with SGLT2i from November 2019 to October 2022. Among 46 final cohorts treated preoperatively with SGLT2i, 29 (63%) developed postoperative metabolic complications. Of these 46 patients, stratified into two categories based on postoperative laboratory findings, risk factor analysis were conducted and compared. Analysis indicated a prescription duration over one week significantly elevated the risk of complications (Unadjusted OR, 11.7; p = 0.032*; Adjusted OR, 31.58; p = 0.014*). A subgroup analysis showed that a cardiopulmonary bypass duration of 60 min or less significantly raises the risk of SGLT2i-related postoperative MA in patients with a sufficient prescription duration. We omitted the term "diabetes" in describing complications related to SGLT2i, as these issues are not exclusive to T2D patients. Awareness of SGLT2i-related postoperative MA or KA can help clinicians distinguish between non-life-threatening conditions and severe causes, thereby preventing unnecessary tests and ensuring best practice.

Idiopathic pulmonary fibrosis (IPF) is a chronic inflammatory and fibrotic response-driven lung disease that is difficult to cure because it manifests excessive profibrotic cytokines (e.g., TGF-β), activated myofibroblasts, and accumulated extracellular matrix (ECM). In an attempt to develop an inhalation formulation with enhanced antifibrotic efficacy, we sought to fabricate unique aerosolizable inhaled microgels (μGel) that contain nintedanib-poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs; n-PN) and pirfenidone-liposomes (p-LP). The aero-μGel was ∼12 μm, resisted phagocytosis by alveolar macrophages in vitro and in vivo, and protected inner-entrapped n-PN and p-LP. The n-PN/p-LP@aero-μGel caused enhanced/extended antifibrotic efficacy in a bleomycin-induced pulmonary fibrosis mouse presumably due to prolonged lung residence. Consequently, the results obtained by intratracheal aerosol insufflation of our n-PN/p-LP@aero-μGel twice a week were much better than those by as many as seven doses of single or mixed applications of n-PN or p-LP. The antifibrotic/pharmacokinetic results for the n-PN/p-LP@aero-μGel included reduced fibrosis progression, restored lung physiological functions, deactivated myofibroblasts, inhibited TGF-β progression, and suppressed ECM component production (collagen I and α-SMA) along with prolonged lung retention time. We believe that our n-PN/p-LP@aero-μGel increased the local availability of both nintedanib and pirfenidone due to evasion of alveolar macrophage phagocytosis and prolonged lung retention with reduced systemic distribution. Through this approach, our inhalation formulation subsequently attenuated fibrosis progression and improved lung function. Importantly, these results hold profound implications in the therapeutic potential of our n-PN/p-LP@aero-μGel to serve as a clinically promising platform, providing significant advancements for improved treatment of many respiratory diseases including IFP.

Many diverse phenomena in nature often inherently encode both short- and long-term temporal dependencies, which especially result from the direction of the flow of time. In this respect, we discovered experimental evidence suggesting that interrelations of these events are higher for closer time stamps. However, to be able for attention-based models to learn these regularities in short-term dependencies, it requires large amounts of data, which are often infeasible. This is because, while they are good at learning piece-wise temporal dependencies, attention-based models lack structures that encode biases in time series. As a resolution, we propose a simple and efficient method that enables attention layers to better encode the short-term temporal bias of these data sets by applying learnable, adaptive kernels directly to the attention matrices. We chose various prediction tasks for the experiments using Electronic Health Records (EHR) data sets since they are great examples with underlying long- and short-term temporal dependencies. Our experiments show exceptional classification results compared to best-performing models on most tasks and data sets.

Aim: We assessed the efficacy of anti-hyperkalemic agents for alleviating hyperkalemia and improving clinical outcomes in patients with out-of-hospital cardiac arrest (OHCA). Methods: This was a single-center, retrospective observational study of OHCA patients treated at tertiary hospitals between 2010 and 2020. Adult patients aged 18 or older who were in cardiac arrest at the time of arrival and had records of potassium levels measured during cardiac arrest were included. A linear regression model was used to evaluate the relationship between changes in potassium levels and use of anti-hyperkalemic medications. Cox proportional hazards regression analysis was performed to analyze the relationship between the use of anti-hyperkalemic agents and the achievement of return of spontaneous circulation (ROSC). Results: Among 839 episodes, 465 patients received anti-hyperkalemic medication before ROSC. The rate of ROSC was higher in the no anti-hyperkalemic group than in the anti-hyperkalemic group (55.9 % vs 47.7 %, P = 0.019). The decrease in potassium level in the anti-hyperkalemic group from pre-ROSC to post-ROSC was significantly greater than that in the no anti-hyperkalemic group (coefficient 0.38, 95 % confidence interval [CI], 0.13–0.64, P = 0.003). In Cox proportional hazards regression analysis, the use of anti-hyperkalemic medication was related to a decreased ROSC rate in the overall group (adjusted hazard ratio [aHR] 0.66, 95 % CI, 0.54–0.81, P

Abstract Deep-learning approaches with data augmentation have been widely used when developing neuroimaging-based computer-aided diagnosis (CAD) systems. To prevent the inflated diagnostic performance caused by data leakage, a correct cross-validation (CV) method should be employed, but this has been still overlooked in recent deep-learning-based CAD studies. The goal of this study was to investigate the impact of correct and incorrect CV methods on the diagnostic performance of deep-learning-based CAD systems after data augmentation. To this end, resting-state electroencephalogram (EEG) data recorded from post-traumatic stress disorder patients and healthy controls were augmented using a cropping method with different window sizes, respectively. Four different CV approaches were used to estimate the diagnostic performance of the CAD system, i.e., subject-wise CV (sCV), overlapped sCV (oSCV), trial-wise CV (tCV), and overlapped tCV (otCV). Diagnostic performances were evaluated using two deep-learning models based on convolutional neural network. Data augmentation can increase the performance with all CVs, but inflated diagnostic performances were observed when using incorrect CVs (tCV and otCV) due to data leakage. Therefore, the correct CV (sCV and osCV) should be used to develop a deep-learning-based CAD system. We expect that our investigation can provide deep-insight for researchers who plan to develop neuroimaging-based CAD systems for psychiatric disorders using deep-learning algorithms with data augmentation.

Introduction: In this study we aimed to investigate the prognostic accuracy for predicting in-hospital mortality using respiratory Sequential Organ Failure Assessment (SOFA) scores by the conventional method of missing-value imputation with normal partial pressure of oxygen (PaO2)- and oxygen saturation (SpO2)-based estimation methods. Methods: This was a single-center, retrospective cohort study of patients with suspected infection in the emergency department. The primary outcome was in-hospital mortality. We compared the area under the receiver operating characteristics curve (AUROC) and calibration results of the conventional method (normal value imputation for missing PaO2) and six SpO2-based methods: using methods A, B, PaO2 is estimated by dividing SpO2 by a scale; with methods C and D, PaO2 was estimated by a mathematical model from a previous study; with methods E, F, respiratory SOFA scores was estimated by SpO2 thresholds and respiratory support use; with methods A, C, E are SpO2-based estimation for all PaO2 values, while methods B, D, F use such estimation only for missing PaO2 values. Results: Among the 15,119 patients included in the study, the in-hospital mortality rate was 4.9%. The missing PaO2was 56.0%. The calibration plots were similar among all methods. Each method yielded AUROCs that ranged from 0.735–0.772. The AUROC for the conventional method was 0.755 (95% confidence interval [CI] 0.736–0.773). The AUROC for method C (0.772; 95% CI 0.754–0.790) was higher than that of the conventional method, which was an SpO2-based estimation for all PaO2 values. The AUROC for total SOFA score from method E (0.815; 95% CI 0.800–0.831) was higher than that from the conventional method (0.806; 95% CI 0.790–0.822), in which respiratory SOFA was calculated by the predefined SpO2 cut-offs and oxygen support. Conclusion: In non-ICU settings, respiratory SOFA scores estimated by SpO2 might have acceptable prognostic accuracy for predicting in-hospital mortality. Our results suggest that SpO2-based respiratory SOFA score calculation might be an alternative for evaluating respiratory organ failure in the ED and clinical research settings.

Physics-Informed Neural Network (PINN) has emerged as a promising tool for solving various physical problems with differential equations. However in practice, PINN often suffers from the local minima issue while solving problems with minimal initial conditions. In this paper, we propose a robust Gated-PINN to address this issue, which blends numerical methods and PINN. The Gated-PINN overcomes the local minima issue by controlling the flow of information of the neural network similar to a numerical method. We first investigate the use of conventional PINN to the Cartesian-coordinate simple pendulum problem with minimal initial conditions, as one of basic differential algebraic equation (DAE) problem. Our results show the advantage of PINN over existing numerical methods in that it does not require sophisticated mathematical techniques such as index reduction. But we also observe that conventional PINN can lead to inaccurate solutions; such solutions partially satisfy the differential equation requirement, but does not meet the given initial condition and fail to further improve. We demonstrate the effectiveness of the proposed Gated-PINN by showing that it yields accurate solutions, such that for a pendulum of length 1, the mean Euclidean error between the Gated-PINN model and the traditional numerical method model is less than 0.01 and pointwise maximum Euclidean error is less than 0.04. Moreover, Gated-PINN can operate without any complicated index reduction, and unlike conventional PINN, accurate solution can be obtained consistently without falling into a local minima. Overall, our study presents the potential of the Gated-PINN for solving DAE problems and provides a valuable insight into the challenges and limitations of using PINN for solving physical problems.

Currently, coating with anti-reflective materials is an attractive approach to improve the quality of screen-based displays. In this study, mesoporous silica particles were systematically synthesized as a function of surfactant (i.e., CTAC-cetyltrimethylammonium chloride) concentration to serve as main coating fillers possessing low refractive indices. Precisely changing the amount of the CTAC surfactant, silica sol with an average diameter of 50 nm exhibits distinctively different specific surface areas, pore size, and pore volume. Prior to the preparation of final coating solutions containing these silica particle fillers, the percentage of solid content was optimized on a glass slide. The use of 50 wt% solid content exhibited the highest transmittance of light. Among various content levels of silica sol, the use of 3.5 wt% of silica particles in the solid content displayed the highest transmittance (i.e., best anti-reflectiveness). Under the almost identical coating layers prepared with the fixed amount of silica particles possessing different surface areas, pore size, and pore volume, it appears that the largest pore volume played the most important role in improving the anti-reflective properties. Experimentally understanding the key feature of low-refractive filler materials under the optimized conditions could provide a clear view to develop highly effective anti-reflective materials for various display applications.

Inspired by erythrocytes that contain oxygen-carrying hemoglobin (Hb) and that exhibit photo-driven activity, we introduce homogenous-sized erythrocyte-like Hb microgel (μGel) systems (5–6 μm) that can (i) emit heat, (ii) supply oxygen, and (iii) generate reactive oxygen species (ROS; 1O2) in response to near-infrared (NIR) laser irradiation. Hb μGels consist of Hb, bovine serum albumin (BSA), chlorin e6 (Ce6) and erbium@lutetium upconverting nanoparticles (UCNPs; ∼35 nm) that effectively convert 808 nm NIR light to 660 nm visible light. These Hb μGels are capable of releasing oxygen to help generate sufficient reactive oxygen species (1O2) from UCNPs/Ce6 under severely hypoxic condition upon NIR stimulation for efficient photodynamic activity. Moreover, the Hb μGels emit heat and increase surface temperature due to NIR light absorption by heme (iron protoporphyrin IX) and display photothermal activity. By changing the Hb/UCNP/Ce6 ratio and controlling the amount of NIR laser irradiation, it is possible to formulate bespoke Hb μGels with either photothermal or photodynamic activity or both in the context of combined therapeutic effect. These Hb μGels effectively suppress highly hypoxic 4T1 cell spheroid growth and xenograft mice tumors in vivo.

Objectives: Heart rate turbulence (HRT) and T-wave alternans (TWA), non-invasive markers of cardiac autonomic dysfunction, and ventricular repolarization abnormality, reportedly, predict the risk of cardiovascular death after myocardial infarction. We investigated whether pre-operative assessment of HRT and/or TWA could predict long-term mortality following coronary artery bypass graft (CABG) surgery. Methods: From May 2010 to December 2017, patients undergoing elective CABG and receiving 24 h ambulatory electrocardiogram monitoring 1 to 5 days prior to CABG surgery were prospectively enrolled. Pre-operative HRT and TWA were measured using a 24 h ambulatory electrocardiogram. The relative risk of cardiac or overall death was assessed according to abnormalities of HRT, TWA, or left ventricular ejection fraction (LV EF). Results: During the mean follow-up period of 4.6 ± 3.9 years, 40 adjudicated overall (5.9%/yr) and 5 cardiac deaths (0.9%/yr) occurred in 146 enrolled patients (64.9 ± 9.3 years; 108 males). Patients with abnormal HRT exhibited significantly higher relative risks of cardiac death (adjusted hazard ratio [HR] 24.9, 95% confidence interval [CI] 1.46–427) and all-cause death (adjusted HR 5.77, 95% CI 2.34–14.2) compared to those with normal HRT. Moreover, abnormal HRT plus abnormal TWA and LV EF < 50% was associated with a greater elevation in cardiac and overall mortality risk. The predictive role of abnormal HRT with/without abnormal TWA for all-cause death was likely more prominent in patients with mildly reduced (35 to 50%) or preserved (≥50%) LV EF. Abnormal HRT plus abnormal TWA and LV EF < 50% showed high negative predictive value in cardiac and overall mortality risk. Conclusions: Assessment of pre-operative HRT and/or TWA predicted mortality risk in patients undergoing elective CABG. Combined analysis of HRT, TWA, and LVEF enhanced the prognostic power. In particular, the predictive value of HRT was enhanced in patients with preserved or mid-range LV EF.