OR-016 Inflammatory responses associated with cortisol and CK after intensive endurance exercise

Objective The aim of this study was  to investigate the effect of acute intensive endurance exercise on circulating leucocyte and cytokine levels in trained kayakers, and to explore inflammatory responses associated with stress hormone and muscle damage. Methods Nine male trained kayakers (average age 21.00±3.94 years, average training history 5.56±1.88 years, average height 187.70±4.69 cm, average weight 89.25±8.66 kg, average body fat% 10.96±4.15%, and average VO2max 4.33±0.62 l/min ) participated in this study. All participants were well informed with the procedures and gave written informed consent. All participats completed a 3000m runing test 2 h after a normal breakfast. Participants were rested for 24 h prior to the exercise test, and kept fasting in 90 min after running test, but drunk water ad arbitrium. Mean heart rate was recorded by a Polar heart rate meter, the earlobe capillary blood lactate was tested with a portable lactate analyzer 3 min after running. Venous blood samples were taken from antecubital vein before (T0) , 15 min (T1) and 90 min (T2) after exercise. Whole blood samples were used for leucocyte counting and its subpopulation counting immediately by Coulter Counter， CD3+, CD4+, CD8+, CD4+ /CD8+, natural killer cells (NK) was evaluated by flow cytometry (Beckman Coulter), T cells were defined as CD3+ lymphocytes and NK was defined as CD3-CD16+CD56+ lymphocyte. Plasma and serum were isolated at 4oC. Plasma ACTH and serum testosterone, cortisol were assayed by CLIA (Immulite 2000), Serum IL-4, IL-6 were detected by ELISA (ST-360). Serum creatine kinase (CK) was assayed by autoanalyzer (Beckman CoulterAU680). Post-exercise concentrition of parameters in plasma and serum was corrected according to the formula by Dill. The data was analysed by IBM SPSS Statistics for Windows, Version 21.0. Continuous variables with normal distribution were presented as mean±standard deviation. Differences between the 3 time points were tested using repeated measures analysis of variance. To classicfy immune−endocrine relationships and  immune−muscle damage relationships, changes of inflammatory parameters were analysed in relation to testosterone, cortisol, ACTH and CK using Pearson's correlation coefficient respectively. Correlation between changes of testosterone, cortisol, ACTH and inflammatory parameters was tested to verify stress hormone related inflammation reponse, correlation between changes of CK and inflammatory parameters was tested to evaluate muscle damage related inflammation response. Only changes which from T1 or T2 differ significantly from T0, and from T1 differ significantly from T2 were included in the correlation analysis. The level of significance was set at p≤0.05. Results Paticipants finished 3000m running with an average time of 715 ± 33.0 Sec, and the average heart rate was 167.00±12.88 b/min, Blood lactate concentration was 12.31±1.91 mmol/l. The result showed significant increases for serum cortisol, serum CK, NK, neutrophile granulocyte% ( GR%), and significant deccreases for testosterone, CD4+, CD4+/CD8+, lymphocyte% (LY%) immedialtly after intensive running. Change of leucocyte count was not significant as a result of inceased NK, GR and decreased CD4+, LY. Compared with result of T1, significant increases of CD4+/CD8+, CD4+, leucocyte count, GR%, and significant decreases of ACTH, cortisol, CD8+, CD3+, LY% were observed at T2, leucocyte count increased with a trend for GR. Furthermore, compared the results of T2 with that of T0, participants presented increased CD4+/CD8+, CK, leucocyte, GR% and decreased testoterone, cortisol, ACTH, CD8+, CD3+, LY%, monocyte% (MO%) at T2. Compared all the levels of IL-4 and IL-6 at T0,T1 and T2 with each other, differences between any two were not significant. The time course of the changes revealed that significantly increased cortisol, NK and decreased CD4+ from T0 to T1, which reovered at T2 compared with T0 were fast response and fast recovery (FR-FR) parameters; Significantly increased CK, CD4+/CD8+, GR%, MO% and decreased testosterone,  LY% from T0 to T1, which didn’t reovered at T2 compared with T0 were fast response and slow recovery (FR-SR) parameters; Significantly increased leucocyte from T0 to T2 and decreased ACTH, CD3+, CD8+ from T1 to T2 were slow response and slow recovery (SR-SR) parameters; IL-4 and IL-6 were nonsensitive response (NR) parameters. Signifcant correlation was observed between ΔcortisolT1-T0 and ΔNKT1-T0 (r=0.78, p=0.04), ΔcortisolT2-T1 and ΔleucocyteT2-T1  (r=-0.70, p=0.04),  ΔACTHT2-T1 and ΔleucocyteT2-T1 (r=-0.76, p=0.02), ΔACTHT2-T0 and ΔCD8+T2-T0 (r=-0.79, p=0.03). No changes (ΔT1-T0, ΔT2-T1, ΔT2-T0) of inflammatory parameters correlated significantly to changes of testosterone and CK. But the correlation analysis revealed a signifcant correlation between ΔCKpost-exercise and Δcortisolpost-exercise (ΔT2-T1, r=0.90, p=0.001; ΔT2-T0, r=0.78, p=0.01). Conclusions Findings demonstrate different time-course responses and recovery of inflammatory parameters to intensive endurance exercise,athletes and coaches should consider these　different recovery time-courses in the subsenquent training session after intensive endurance training. Correlation analysis between cortisol, CK and inflammatory parameters indicates that inflammatory response is a stress hormone other than a muscle damage tuned process, and on the contrary, the correlation between post-exercise changes of CK and cortisol suggests a hint that inflammatory response caused by cortisol may contribute to the post-exercise muscle damage but not that during exercising. Correlation analysis and time-course analysis reveal that cortisol exerting an acute effect on NK, but maybe a false time-lag effect on leucocyte. This research investigated the inflammatory reponses to intensive endurance exercise by correlation analysis, but inflammary reponse is a multifactor process, and the conclusion is still challenging, further research is necessary to understand the underlying mechanism

Deep Learning for Logo Detection: A Survey

When logos are increasingly created, logo detection has gradually become a research hotspot across many domains and tasks. Recent advances in this area are dominated by deep learning-based solutions, where many datasets, learning strategies, network architectures, etc. have been employed. This paper reviews the advance in applying deep learning techniques to logo detection. Firstly, we discuss a comprehensive account of public datasets designed to facilitate performance evaluation of logo detection algorithms, which tend to be more diverse, more challenging, and more reflective of real life. Next, we perform an in-depth analysis of the existing logo detection strategies and the strengths and weaknesses of each learning strategy. Subsequently, we summarize the applications of logo detection in various fields, from intelligent transportation and brand monitoring to copyright and trademark compliance. Finally, we analyze the potential challenges and present the future directions for the development of logo detection to complete this survey

Ultrasound Versus Contrast-Enhanced Magnetic Resonance Imaging for Subclinical Synovitis and Tenosynovitis: A Diagnostic Performance Study

OBJECTIVES: Radiographic manifestations of synovitis (e.g., erosions) can be observed only in the late stage of rheumatoid arthritis. Ultrasound is a noninvasive, cheap, and widely available technique that enables the evaluation of inflammatory changes in the peripheral joint. In the same way, dynamic contrast-enhanced magnetic resonance imaging (MRI) enables qualitative and quantitative measurements. The objectives of the study were to compare the sensitivity and accuracy of ultrasound in detecting subclinical synovitis and tenosynovitis with those of contrast-enhanced MRI. METHODS: The ultrasonography and contrast-enhanced MRI findings of the wrist, metacarpophalangeal, and proximal interphalangeal joints (n=450) of 75 patients with a history of joint pain and morning stiffness between 6 weeks and 2 years were reviewed. The benefits score was evaluated for each modality. RESULTS: The ultrasonic findings showed inflammation in 346 (77%) joints, while contrast-enhanced MRI found signs of early rheumatoid arthritis in 372 (83%) joints. The sensitivities of ultrasound and contrast-enhanced MRI were 0.795 and 0.855, respectively, and the accuracies were 0.769 and 0.823, respectively. Contrast-enhanced MRI had a likelihood of 0–0.83 and ultrasound had a likelihood of 0–0.77 for detecting synovitis and tenosynovitis at one time. The two imaging modalities were equally competitive for detecting synovitis and tenosynovitis (p=0.055). CONCLUSION: Ultrasound could be as sensitive and specific as contrast-enhanced MRI for the diagnosis of subclinical synovitis and tenosynovitis

The α1‐adrenergic receptor is involved in hepcidin upregulation induced by adrenaline and norepinephrine via the STAT3 pathway

Elevated body iron stores are associated with hypertension progression, while hypertension is associated with elevated plasma catecholamine levels in patients. However, there is a gap in our understanding of the connection between catecholamines and iron regulation. Hepcidin is a key iron‐regulatory hormone, which maintains body iron balance. In the present study, we investigated the effects of adrenaline (AD) and norepinephrine (NE) on hepatic hepcidin regulation. Mice were treated with AD, NE, phenylephrine (PE, α1‐adrenergic receptor agonist), prazosin (PZ, α1‐adrenergic receptor antagonist), and/or propranolol (Pro, β‐adrenergic receptor antagonist). The levels of hepcidin, as well as signal transducer and activator of transcription 3 (STAT3), ferroportin 1 (FPN1), and ferritin‐light (Ft‐L) protein in the liver or spleen, were assessed. Six hours after AD, NE, or PE treatment, hepatic hepcidin mRNA levels increased. Pretreatment with PZ, but not Pro, abolished the effects of AD or NE on STAT3 phosphorylation and hepatic hepcidin expression. When mice were treated with AD or NE continuously for 7 days, an increase in hepatic hepcidin mRNA levels and serum hepcidin concentration was also observed. Meanwhile, the expected downstream effects of elevated hepcidin, namely decreased FPN1 expression and increased Ft‐L protein and non‐heme iron concentrations in the spleen, were observed after the continuous AD or NE treatments. Taken together, we found that AD or NE increase hepatic hepcidin expression via the α1‐adrenergic receptor and STAT3 pathways in mice. The elevated hepatic hepcidin decreased FPN1 levels in the spleen, likely causing the increased iron accumulation in the spleen

Guilotes, a new genus of Coelotinae spiders from Guangxi Zhuang Autonomous Region, China (Araneae, Agelenidae)

A new genus of the subfamily Coelotinae F.O. Pickard-Cambridge, 1893, Guilotes Z. Zhao & S. Li, gen. n. from China is described, as well as four new species: G. ludiensis Z. Zhao & S. Li, sp. n. (♂♀, type species), G. qingshitanensis Z. Zhao & S. Li, sp. n. (♂♀), G. xingpingensis Z. Zhao & S. Li, sp. n. (♂♀) and G. yandongensis Z. Zhao & S. Li, sp. n. (♀). The DNA barcodes of all species are documented for future use

2D, 3D-QSAR study and docking of vascular endothelial growth factor receptor 3 (VEGFR3) inhibitors for potential treatment of retinoblastoma

Background: Retinoblastoma is currently the most common malignant tumor seen in newborns and children’s eyes worldwide, posing a life-threatening hazard. Chemotherapy is an integral part of retinoblastoma treatment. However, the chemotherapeutic agents used in clinics often lead to drug resistance. Thus there is a need to investigate new chemotherapy-targeted agents. VEGFR3 inhibitors are anti-tumour-growth and could be used to develop novel retinoblastoma-targeted agents.Objective: To predict drug activity, discover influencing factors and design new drugs by building 2D, 3D-QSAR models.Method: First, linear and non-linear QSAR models were built using heuristic methods and gene expression programming (GEP). The comparative molecular similarity indices analysis (COMISA) was then used to construct 3D-QSAR models through the SYBYL software. New drugs were designed by changing drug activity factors in both models, and molecular docking experiments were performed.Result: The best linear model created using HM had an R2, S2, and R2cv of 0.82, 0.02, and 0.77, respectively. For the training and test sets, the best non-linear model created using GEP had correlation coefficients of 0.83 and 0.72 with mean errors of 0.02 and 0.04. The 3D model designed using SYBYL passed external validation due to its high Q2 (0.503), R2 (0.805), and F-value (76.52), as well as its low standard error of SEE value (0.172). This demonstrates the model’s reliability and excellent predictive ability. Based on the molecular descriptors of the 2D model and the contour plots of the 3D model, we designed 100 new compounds using the best active compound 14 as a template. We performed activity prediction and molecular docking experiments on them, in which compound 14.d performed best regarding combined drug activity and docking ability.Conclusion: The non-linear model created using GEP was more stable and had a more substantial predictive power than the linear model built using the heuristic technique (HM). The compound 14.d designed in this experiment has the potential for anti-retinoblastoma treatment, which provides new design ideas and directions for retinoblastoma-targeted drugs