The E3 ubiquitin ligase MARCH2 protects against myocardial ischemia-reperfusion injury through inhibiting pyroptosis via negative regulation of PGAM5/MAVS/NLRP3 axis.

Inflammasome activation and pyroptotic cell death are known to contribute to the pathogenesis of cardiovascular diseases, such as myocardial ischemia-reperfusion (I/R) injury, although the underlying regulatory mechanisms remain poorly understood. Here we report that expression levels of the E3 ubiquitin ligase membrane-associated RING finger protein 2 (MARCH2) were elevated in ischemic human hearts or mouse hearts upon I/R injury. Genetic ablation of MARCH2 aggravated myocardial infarction and cardiac dysfunction upon myocardial I/R injury. Single-cell RNA-seq analysis suggested that loss of MARCH2 prompted activation of NLRP3 inflammasome in cardiomyocytes. Mechanistically, phosphoglycerate mutase 5 (PGAM5) was found to act as a novel regulator of MAVS-NLRP3 signaling by forming liquid-liquid phase separation condensates with MAVS and fostering the recruitment of NLRP3. MARCH2 directly interacts with PGAM5 to promote its K48-linked polyubiquitination and proteasomal degradation, resulting in reduced PGAM5-MAVS co-condensation, and consequently inhibition of NLRP3 inflammasome activation and cardiomyocyte pyroptosis. AAV-based re-introduction of MARCH2 significantly ameliorated I/R-induced mouse heart dysfunction. Altogether, our findings reveal a novel mechanism where MARCH2-mediated ubiquitination negatively regulates the PGAM5/MAVS/NLRP3 axis to protect against cardiomyocyte pyroptosis and myocardial I/R injury.

FUNDC1 interacts with GPx4 to govern hepatic ferroptosis and fibrotic injury through a mitophagy-dependent manner.

INTRODUCTION: Liver fibrosis is a life-threatening pathological anomaly which usually evolves into advanced liver cirrhosis and hepatocellular carcinoma although limited therapeutic option is readily available. FUN14 domain containing 1 (FUNDC1) is a mitophagy receptor with little information in liver fibrosis. OBJECTIVE: This study was designed to examine the role for FUNDC1 in carbon tetrachloride (CCl4)-induced liver injury. METHODS: GEO database analysis and subsequent validation of biological processes including western blot, immunofluorescence, and co-immunoprecipitation were applied to clarify the regulatory role of FUNDC1 on mitophagy and ferroptosis. RESULTS: Our data revealed elevated FUNDC1 levels in liver tissues of patients with liver fibrotic injury and CCl4-challenged mice. FUNDC1 deletion protected against CCl4-induced hepatic anomalies in mice. Moreover, FUNDC1 deletion ameliorated CCl4-induced ferroptosis in vivo and in vitro. Mechanically, FUNDC1 interacted with glutathione peroxidase (GPx4), a selenoenzyme to neutralize lipid hydroperoxides and ferroptosis, via its 96-133 amino acid domain to facilitate GPx4 recruitment into mitochondria from cytoplasm. GPx4 entered mitochondria through mitochondrial protein import system-the translocase of outer membrane/translocase of inner membrane (TOM/TIM) complex, prior to degradation of GPx4 mainly through mitophagy along with ROS-induced damaged mitochondria, resulting in hepatocyte ferroptosis. CONCLUSION: Taken together, our data favored that FUNDC1 promoted hepatocyte injury through GPx4 binding to facilitate its mitochondrial translocation through TOM/TIM complex, where GPx4 was degraded by mitophagy to trigger ferroptosis. Targeting FUNDC1 may be a promising therapeutic approach for liver fibrosis.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.

Neutrophil to high-density lipoprotein cholesterol ratio predicts adverse cardiovascular outcomes in subjects with pre-diabetes: a large cohort study from China.

BACKGROUND: This study aimed to examine whether the neutrophil to high-density lipoprotein cholesterol ratio (NHR) can predict cardiovascular outcomes in normoglycemic individuals with elevated fasting glucose levels. METHODS: A total of 130,801 participants with normal blood glucose levels were enrolled in the Kailuan study. Participants were categorized according to NHR quartiles and further divided into normal glucose regulation (NGR) and pre-diabetes (pre-DM) subgroups. The follow-up endpoint was major adverse cardiovascular events (CVE), including stroke and myocardial infarction. RESULTS: Over a median of 12.53 (8.95-13.08) years of follow-up, subjects with NHR levels in the highest quartile experienced more CVE than those with NHR levels in the lowest quartile. Multivariate Cox analyses showed that continuous changes in NHR (hazard ratio, 1.21; 95% confidence interval [CI], 1.15-1.28) and the highest quartile of NHR (hazard ratio, 1.30; 95% CI, 1.21-1.39) were independent predictors of CVE (all P < 0.001). Furthermore, when participants were categorized by both NHR quartile and glucose metabolism status, the NHR level in the highest quartile plus pre-DM group was associated with a 1.60-fold (95% CI, 1.38-1.86; P < 0.001] higher risk of CVE than that in the lowest quartile plus normoglycemic group. Significantly, the addition of NHR only, presence of pre-DM only, or combination of NHR and pre-DM to the prediction algorithm, including traditional risk factors, improved the C-statistic by 0.19, 0.05, and 0.23 (all P < 0.001). CONCLUSIONS: Elevated NHR or fasting blood glucose level were independently associated with a higher risk of CVE among normoglycemic individuals. Moreover, pre-DM participants with high NHR levels tended to have worse prognosis, suggesting that NHR could provide greater risk stratification value than traditional risk factors for subjects with pre-DM.

Severity of Nonalcoholic Fatty Liver Disease is Associated With Cardiovascular Outcomes in Patients With Prehypertension or Hypertension: A Community-Based Cohort Study.

Background: It is unclear whether more severe non-alcoholic fatty liver disease (NAFLD) combined with prehypertension or hypertension is associated with a higher risk of cardiovascular events (CVEs). To evaluate the relationship between the severity of NAFLD and CVEs among patients with prehypertension or hypertension. Methods: In this prospective community-based Kailuan cohort, participants without cardiovascular disease and alcohol abuse, or other liver diseases were enrolled. NAFLD was diagnosed by abdominal ultrasonography. Prehypertension was defined as systolic blood pressure (BP) of 120-139 mmHg or diastolic BP of 80-89 mmHg. Participants with NAFLD were divided into mild, moderate, and severe subgroups. Follow-up for CVEs including myocardial infarction, hemorrhagic stroke, and ischemic stroke. The Cox proportional hazards model was used to estimate hazard ratios and 95% CIs of CVEs according to the severity of NAFLD and hypertensive statutes. The C-statistic was used to evaluate the efficiency of models. Results: A total of 71926 participants (mean [SD] age, 51.83 [12.72] years, 53794 [74.79%] men, and 18132 [25.21%] women) were enrolled in this study, 6,045 CVEs occurred during a median of 13.02 (0.65) years of follow-up. Compared with participants without NAFLD, the hazard ratios of CVEs for patients with mild, moderate, and severe NAFLD were 1.143 (95% CI 1.071-1.221, P < 0.001), 1.218 (95% CI 1.071-1.221, P < 0.001), and 1.367 (95% CI 1.172-1.595, P < 0.001), respectively. Moreover, participants with prehypertension plus moderate/severe NAFLD and those with hypertension plus moderate/severe NAFLD had 1.558-fold (95% CI 1.293-1.877, P < 0.001) and 2.357-fold (95% CI 2.063-2.691, P < 0.001) higher risks of CVEs, respectively, compared with those with normal BP and no NAFLD. Adding a combination of NAFLD and BP status to the crude Cox model increased the C-statistic by 0.0130 (0.0115-0.0158, P < 0.001). Conclusions: Our findings indicated that the increased cardiovascular risk with elevated BP is largely driven by the coexistence of moderate/severe NAFLD, suggesting that the severity of NAFLD may help further stratify patients with prehypertension and hypertension.

Non-alcoholic Fatty Liver Disease Is Associated With Cardiovascular Outcomes in Subjects With Prediabetes and Diabetes: A Prospective Community-Based Cohort Study.

Background: There have been no studies of the effect of non-alcoholic fatty liver disease (NAFLD) on cardiovascular events (CVEs) in patients with pre-diabetes (pre-DM), and diabetes mellitus (DM). We performed a community-based cohort study to evaluate the relationship between NAFLD and CVEs in patients with glucose metabolism disorder. Methods: We enrolled 71,852 participants from the Kailuan study who had not experienced CVEs, after excluding alcohol abuse and other liver diseases. NAFLD was assessed using abdominal ultrasonography. Besides, participants were categorized by glucose metabolism status [normal glucose regulation (NGR), pre-DM, and DM]. All subjects were followed up for the occurrence of CVEs. Results: During a median of 13.01 (0.64) years of follow-up, 6,037 CVEs occurred. NAFLD was present in 22,525 (31.3%), and compared with participants without NAFLD, those with NAFLD had a 12.3% [95% confidence interval (CI) 1.059-1.191, P < 0.001] higher risk of CVEs, after adjustment for potential confounders. The hazard ratios for patients with mild, moderate, and severe NAFLD were 1.104 (95% CI 1.035-1.179, P < 0.001), 1.149 (95% CI 1.055-1.251, P < 0.001), and 1.235 (95% CI 1.059-1.441, P < 0.001), respectively. Moreover, participants with pre-DM plus NAFLD and participants with DM plus NAFLD had 1.267-fold (95% CI 1.151-1.395, P < 0.001) and 1.829-fold (95% CI 1.666-2.008, P < 0.001) higher risks of CVEs, respectively, compared with those with NGR and no NAFLD. The addition of the combination of NAFLD and glucose metabolism status to the crude Cox model increased the C-statistic by 0.0066 (0.0053-0.0080, P < 0.001). Conclusions: NAFLD is associated with higher risks of CVEs. Moreover, NAFLD is an independent predictor of CVEs in patients with pre-DM and DM, suggesting that NAFLD may provide greater risk predictive value for patients with glucose metabolism disorder.

MoNuSAC2020: A Multi-Organ Nuclei Segmentation and Classification Challenge.

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Technical Note: A cascade 3D U-Net for dose prediction in radiotherapy.

PURPOSE: Although large datasets are available, to learn a robust dose prediction model from a limited dataset still remains challenging. This work employed cascaded deep learning models and advanced training strategies with a limited dataset to precisely predict three-dimensional (3D) dose distribution. METHODS: A Cascade 3D (C3D) model is developed based on the cascade mechanism and 3D U-Net network units. During model training, data augmentations are used to improve the generalization ability of the prediction model. A knowledge distillation technique is employed to further improve the capability of model learning. The C3D network was evaluated using the OpenKBP challenge dataset and competed with those models proposed by more than 40 teams globally. Additionally, it was compared with five existing cutting-edge dose prediction models. The performance of these prediction models was evaluated by voxel-based mean absolute error (MAE) and clinical-related dosimetric metrics. The code and models are publicly available online (https://github.com/LSL000UD/RTDosePrediction). RESULTS: The MAE of a single C3D model without test-time augmentation is 2.50 Gy (3.57% related to prescription dose) for nonzero dose area, which outperforms the other five dose prediction models by about 0.1 Gy-1.7 Gy. The C3D model won both dose and DVH streams of AAPM 2020 OpenKBP challenge with dose score of 2.31 and DVH score of 1.55. CONCLUSIONS: The Cascading U-Nets is an ideal solution for 3D dose prediction from a limited dataset. The proper data preprocessing, data augmentation, and optimization procedure are more important than architectural modifications of deep learning network.

Predicting voxel-level dose distributions for esophageal radiotherapy using densely connected network with dilated convolutions.

This work aims to develop a voxel-level dose prediction framework by integrating distance information between PTV and OARs, as well as image information, into a densely-connected network (DCNN). Firstly, a four-channel feature map, consisting of a PTV image, an OAR image, a CT image, and a distance image, is constructed. A densely connected neural network is then built and trained for voxel-level dose prediction. Considering that the shape and size of OARs are highly inconsistent, a dilated convolution is employed to capture features from multiple scales. Finally, the proposed network is evaluated with five-fold cross-validation, based on ninety-eight clinically approved treatment plans. The voxel-level mean absolute error(MAE V ) of DCNN was 2.1% for PTV, 4.6% for left lung, 4.0% for right lung, 5.1% for heart, 6.0% for spinal cord, and 3.4% for body, which outperforms conventional U-Net, Resnet-antiResnet, U-Resnet-D by 0.1-0.8%. This result shows that with the introduction of a distance image and DCNN model, the accuracy of predicted dose distribution could be significantly improved. This approach offers a new dose prediction tool to support quality assurance and the automation of treatment planning in esophageal radiotherapy.

Association of serum lipoprotein(a) level with the severity and prognosis of calcific aortic valve stenosis: a Chinese cohort study.

BACKGROUND: There was a causal relationship between elevated lipoprotein(a) [Lp(a)] levels and increased risk of calcific aortic valve stenosis (CAVS) in whites and blacks. The present study aimed to investigate whether Lp(a) levels were associated with aortic stenosis (AS) severity and clinical events in Chinese patients. METHODS: Levels of serum Lp(a) were measured in 652 patients with CAVS, whom all underwent baseline echocardiographic examination. The clinical endpoint was defined as a composite of aortic valve replacement (AVR) and cardiac death. RESULTS: Patients in the tertile 3 of Lp(a) had a higher percentage of severe AS compared with those in the tertile 1 and 2 of Lp(a) (46.2% vs. 33.9%, P = 0.005). Moreover, the top tertile of Lp(a) was an independent predictor of severe AS (OR = 1.78, 95% CI: 1.18-2.66, P = 0.006). However, there was no significant association between tertile 3 of Lp(a) and clinical events (hazard ratio: 0.73; 95% CI: 0.43-1.24; P = 0.239) in the multivariate Cox regression analysis during a mean follow-up time of 3.16 ± 2.74 years. CONCLUSIONS: Elevated Lp(a) level was an independent predictor of severe AS by echocardiography in the Chinese population, but was not associated with the increased risk of AVR and cardiac death, suggesting that Lp(a) levels might be helpful in the risk stratification of patients with CAVS.

Fibrinogen is associated with glucose metabolism and cardiovascular outcomes in patients with coronary artery disease.

BACKGROUND: The present cohort study aims to examine the relationship between fibrinogen (Fib) levels and glucose metabolism [fasting blood glucose (FBG) and hemoglobin A1c (HbA1c)] and investigate the impact of high Fib on cardiovascular outcomes in patients with stable CAD and pre-diabetes mellitus (pre-DM) or diabetes mellitus (DM). METHODS: This study included 5237 patients from March 2011 to December 2015. Patients were distributed into three groups according to Fib levels (low Fib, median Fib, high Fib) and further categorized by glucose metabolism status [normal glucose regulation (NGR), Pre-DM, DM]. All patients were followed up for the occurrences of major adverse cardiovascular events (MACEs), including cardiovascular mortality, nonfatal MI, stroke, and unplanned coronary revascularization. RESULTS: Linear regression analyses showed that FBG and HbA1c levels were positively associated with Fib in overall CAD participants, either with or without DM (all P < 0.001). During an average of 18,820 patient-years of follow-up, 476 MACEs occurred. High Fib was independently associated with MACEs after adjusting for confounding factors [Hazard Ratio (HR): 1.57, 95% confidence interval (CI) 1.26-1.97, P < 0.001]. Furthermore, DM but not pre-DM was a significant predictor of MACEs (P < 0.001 and P > 0.05, respectively). When patients were stratified by both glucose metabolism status and Fib levels, high Fib was associated with a higher risk of MACEs in pre-DM (HR 1.66, 95% CI 1.02-2.71, P < 0.05). Medium and high Fib levels were associated with an even higher risk of MACEs in DM (HR 1.86, 95% CI 1.14-3.05 and HR 2.28, 95% CI 1.42-3.66, all P < 0.05). After adding the combination of Fib and glucose status to the Cox model, the C-statistic was increased by 0.015 (0.001-0.026). CONCLUSIONS: The present study suggested that Fib levels were associated with FBG and HbA1c in stable CAD patients. Moreover, elevated Fib was independently associated with MACEs in CAD patients, especially among those with pre-DM and DM, suggesting that Fib may provide incremental value in the cardiovascular risk stratification of pre-DM and DM patients.

Lipoprotein(a) and coronary artery disease in Chinese postmenopausal female patients: a large cross-sectional cohort study.

BACKGROUND: It has been reported that lipoprotein(a) (Lp(a)) is associated with the risk of cardiovascular disease. The present study aimed to examine the association of Lp(a) levels with the presence and severity of coronary artery disease (CAD) in female patients. METHODS: A total of 3712 female patients who received coronary angiography were consecutively enrolled. The levels of Lp(a) were measured and compared among patients with or without CAD, myocardial infarction and menopause. Spearman correlation analysis and logistic regression analysis were used to examine the association of Lp(a) with the presence of CAD and the severity of coronary atherosclerosis assessed by Gensini score (GS). RESULTS: The average of Lp(a) levels was elevated as age increased in female subjects. Notably, women after menopause had higher Lp(a) levels compared with that before menopause (16.8 mg/dL (IQR 7.54-41.12 mg/dL) vs 14.7 mg/dL (IQR 6.72-30.82 mg/dL), p=0.002). Furthermore, multiple logistic regression analysis identified that Lp(a)>30 mg/dL was an independent risk factor of CAD in the postmenopausal females (OR: 1.33, 95% CI: 1.08 to 1.63, p=0.007). Finally, Lp(a) had a positive correlation with GS (r=0.11, p<0.001), and Lp(a)>30 mg/dL was an independent risk factor for high GS (OR: 1.43, 95% CI: 1.14 to 1.79, p=0.02) in the postmenopausal females. CONCLUSION: Circulating Lp(a) levels were independently associated with the presence and severity of CAD in the postmenopausal females, suggesting that Lp(a) may be useful for prevention and risk-stratification of CAD in female individuals.

Prognostic Value of Combined C-Reactive Protein, Body Mass Index, and Left Ventricular Ejection Fraction in Predicting Cardiovascular Events in Patients ≥80 Years of Age With Acute Myocardial Infarction.

Elevated high-sensitivity C-reactive protein (hsCRP) and low body mass index (BMI) are linked to increased mortality in the elderly population. However, the combined value for predicting adverse cardiovascular events in the oldest-old (≥80 years old) with acute myocardial infarction (AMI) remains undetermined. A total of 463 AMI patients, who were ≥80 years old, were enrolled in this study between January 2012 and June 2017. A nested case-control study was implemented in 106 deaths and 212 controls, who were matched for age, gender, time of inclusion, and myocardial infarction type. Furthermore, the individual and additive values of hsCRP, BMI, and left ventricular ejection fraction (LVEF) were assessed using adjusted hazard ratio, unadjusted Kaplan-Meier analysis, and receiver-operating characteristic curve models. The median follow-up time was 19.15 months, and there were 106 deaths (33.3%). Furthermore, HsCRP, BMI, and LVEF were significantly associated with all-cause mortality (p <0.05, respectively). In addition, a negative correlation between BMI and LVEF, and the positive association of hsCRP with all-cause mortality in the fully adjusted Cox proportional hazards model were detected. The combination of hsCRP, BMI, and LVEF was found to exhibit an enhanced predictive value for all-cause mortality (0.733 in jointly vs 0.623 in cardiovascular risk factors, p = 0.0007) in these oldest-old AMI patients. HsCRP, BMI, and LVEF are the independent risk factors for all-cause mortality for the oldest-old patients with AMI, and this combination offers more appreciable and reliable predictive value for all-cause mortality.

Association of invasive treatment and lower mortality of patients ≥ 80 years with acute myocardial infarction: a propensity-matched analysis.

OBJECTIVE: To investigate whether invasive strategy was associated with lower mortality in Chinese patients ≥ 80 years with acute myocardial infarction (AMI). METHODS: We used retrospective data from our center between 2013 and 2017. During a median of 17.4 (interquartile range: 7.3-32.3) months follow-up, 120 deaths were recorded among 514 consecutive patients ≥ 80 years with AMI. The patients were divided into two groups: invasive treatment group (IT group, n = 269) and conservative treatment group (CT group, n = 245), which were also then compared with propensity score matching. RESULTS: High mortality was found in CT group compared with that in the IT one. Cox proportional hazard regression analysis showed that invasive treatment was associated with lower mortality of patients ≥ 80 years. Moreover, the results revealed that the patients in IT group had lower in-hospital mortality (3.35% vs. 9.39%, P = 0.005). Besides, the Kaplan-Meier analysis revealed that the mortality was significantly lower in IT group compared with that in CT group using entire and propensity-matched cohort analysis (P < 0.001, respectively). CONCLUSIONS: Our data suggested that IT appeared to be associated with lower mortality in Chinese patients ≥ 80 years with AMI, which consists with previous studies in spite of either ST elevated myocardial infarction (STEMI) or non-STEMI (NSTEMI) patients.

Effect of Resveratrol on Blood Rheological Properties in LPS-Challenged Rats.

Objectives: Abnormal rheological properties induce adverse effects during sepsis. This study sought to investigate the hypothesis that resveratrol (Res) improves blood rheological properties in rats following a lipopolysaccharide (LPS) challenge, and provide a novel approach for treatment of sepsis. Methods: The rats were intraperitoneally or intramuscularly injected with vehicle, LPS (8 mg/kg), Res (30 mg/kg), or both to yield four groups: control, Res, LPS, and LPS + Res. After 6 h of LPS and/or Res injection, the mean arterial pressure (MAP), regional blood flow, erythrocyte and leukocyte parameters, and blood viscosity were observed. Results: LPS administration had no significant effects on the erythrocyte parameters and plasma viscosity. LPS administration reduced the MAP, whole blood viscosity at low and medium shear rates, the blood flow in the spleen and kidney, and the leukocyte content in whole blood when compared to control group, and increased the myeloperoxidase (MPO) activity in lung. Treatment with Res alone had no effects on most of parameters observed except increasing the whole blood relative viscosity. However, Res treatment after LPS resulted in further decrease in whole blood viscosity at high and medium shear rates. Furthermore, Res treatment conversely decreased the red blood cell distribution width-CV, blood flow of stomach, whole blood relative viscosity and MPO activity in lung, and increased the leukocyte content, but did not restore LPS-induced decrease in MAP and the blood flow in the spleen and kidney. Conclusion: The Res treatment partly reduce the whole blood viscosity and regional blood flow, and increase WBC content in peripheral blood following the LPS challenge, suggesting a favorable role in expanding the quasi-sympathetic effects of LPS in blood viscosity at early stages.