Platelet to lymphocyte ratio (PLR) was recently reported as a useful index in predicting the prognosis of lung cancer. However, the prognostic role of PLR in lung cancer remains controversial. The aim of this study was to evaluate the association between PLR and clinical outcome of lung cancer patients through a meta-analysis. Relevant literatures were retrieved from PubMed, Ovid, the Cochrane Library and Web of Science databases. Meta-analysis was performed using hazard ratio (HR) and 95% confidence intervals (CIs) as effect measures. A total of 5,314 patients from 13 studies were finally enrolled in the meta-analysis. The summary results showed that elevated PLR predicted poorer overall survival (OS) (HR: 1.526, 95%CI: 1.268-1.836, p < 0.001) in patients with lung cancer and OS (HR: 1.631, 95%CI: 1.447-1.837, p < 0.001) in patients with nonsmall cell lung cancer (NSCLC). Subgroup analysis revealed that increased PLR was also associated with poor OS in NSCLC treated by surgical resection (HR: 1.884, 95%CI: 1.308-2.714, P < 0.001) and non-surgery (HR: 1.570, 95%CI: 1.323-1.863, P < 0.001). In addition, PLR Cut-off value ≤ 160 (HR: 1.506, 95%CI: 1.292-1.756, P < 0.001) and PLR Cut-off value>160 (HR: 1.842, 95%CI: 1.523-2.228, P < 0.001). In contrast, elevated PLR was not associated with OS (HR: 1.117, 95%CI: 0.796-1.569, P > 0.05) in patients with small cell lung cancer (SCLC).This meta-analysis result suggested that elevated PLR might be a predicative factor of poor prognosis for NSCLC patients.
This study aimed to examine the effect of football shoes with different collar types on ankle and knee kinematic and kinetics features during 45° and 135° side-step cutting tasks. Fifteen healthy college football players volunteered for the study. Each participant was instructed to perform side-step cutting tasks with high, low, and no collar football shoes. The kinematic and ground reaction force data were measured using a Vicon motion capture system and a Kistler force plate, respectively. Two-way MANOVAs with repeated measures were used to examine the effect of shoe collar type and task conditions. There were no interaction effects. The high collar football shoe showed decreased ankle range of motion in the sagittal plane (p = 0.010) and peak ankle external rotation moment (p = 0.009) compared to the no collar football shoe. The high (p = 0.025) and low (p = 0.029) collar football shoes presented greater peak ankle external rotation angles than the no collar football shoe. These results imply that football shoes with high collars made of high intensity knitted fabric could be used to restrict ankle joint movement, with potential implications for decreasing the risk of ankle sprain injuries in football players.
In order to explore dissolved organic matter (DOM) components and their origins in metropolitan lakes and reservoirs in the karst region, the typical Hongfeng Lake, Baihua Lake, Songbaishan Reservoir, and Aha Reservoir were investigated in Guiyang City. Surface water parameters, including dissolved organic carbon (DOC), chlorophyll a (Chla), and optical parameters (a254, a280, a350, E2:E3, S275-295, FI, β:α, BIX, and HIX) were analyzed. Fluorescence peaks (B, T, A, M, C, D, and N) and three-dimensional matrix fluorescence with parallel factor analysis (EEM-PARAFAC) were employed to explain distinct DOM abundances and proportions. Meanwhile, Spearman's correlation coefficients and principal component analysis (PCA) were used to decipher parameter types and primary environmental processes. The results showed that aquatic ρ(DOC) and ρ(Chla) ranged between 4.24-11.9 mg·L-1 and 0.32-19.7 μg·L-1, respectively. High humic-like (a254) and protein DOM (a280) were observed in the Songbaishan Reservoir, resulting in higher DOM molecular weight when compared to that in other lakes and reservoirs. Surface water DOM mainly contained visible-light humic-like (23.8%-46.9%) and terrestrial fulvic-like components (17.6%-28.4%). High FI, β:α, and BIX but low HIX values in this study suggested that endogenous inputs largely contributed to aquatic DOM. Aquatic DOM component and source characteristics were significantly correlated with each other. Furthermore, inputs of humic-like DOM and microbial metabolism, as well as coupled carbonate dissolution and photosynthesis, drove dynamic DOM behaviors in the karst lakes and reservoirs.
Objective To explore the feasibility of real-time monitoring exposure dose and image quality by using the data stored in the DICOM image archive of direct digital radiography system.Methods Model TO.16 was exposed,the current increased gradually from 0.5 to 125 mAs.The displayed number of model A(diameter 11.1 mm),D (diameter 4.0 mm) and J(diameter 0.7 mm) were recorded,and the detect factors(H_T)was also calculated.Images were sent to workstation before the end of DR examination.An automatic procedure was implemented to extract dose data and exposure parameters from the DICOM header file. Maximum,minimum and 3rd quartile values were preinstalled. Mean values exceeding the threshold trigger alarm signal to guide radiologist to explore the cause.Results When the current of point A was less than 10 mAs and the current of point D and J were less than 16 mAs,the detect factor(HT)increased with the rise of current.While point A located within 10-100 mAs,point D and J within 16-100 mAs,the detect factor did not rise.Totally,66 alarm signals were observed among 5120 exposures including 21 alarm signals triggered by the exceeded dose limit,among which,7 signals triggered by manual control overdose,4 signals triggered by selection faults related to auto exposure control (AEC),9 signals resulted from the increased exposure field and one unclear signal associated with the instability of AEC during short period.The other 45 alarm signals were triggered by the below dose limit due to the examination position not at the centre.Conclusion The adopted method can detect inappropriate exposure dose and impaired picture quality caused by technician or equipment,therefore it can real-time manage exposure dose and image quality automatically.
Key words:
Radiography; Radiation monitoring
High-osmolarity glycerol (HOG) pathway required for yeast osmoregulation relies upon the mitogen-activated protein kinase (MAPK) Hog1 cascade that comprise the MAPKKKs Ssk2/Ssk22 and Ste11 converging on the MAPKK Pbs2. Here we show a Hog1 cascade with the unique MAPKKK Ssk2 acting in Beauveria bassiana. Hypersensitivity to high osmolarity and high resistance to fludioxonil fungicide appeared in Δssk2, Δpbs2 and Δhog1 mutants whereas the two hallmark phenotypes were reversed in Δste11. Increased sensitivity to heat shock and decreased sensitivity to cell wall perturbation also occurred in the three mutants but not in Δste11 although antioxidant phenotypes were different in all deletion mutants. Intriguingly, signals of Hog1 phosphorylation induced by osmotic, oxidative and thermal cues were present in Δste11 but absent in Δssk2 and Δpbs2. Moreover, vegetative growth on minimal media with different carbon/nitrogen sources was much more suppressed in Δste11 and Δssk2 than in Δpbs2 and Δhog1 although all mutants suffered similar, but severe, conidiation defects on a standard medium. Normal host infection was abolished in Δste11 while virulence was differentially attenuated in other mutants. Our findings exclude Ste11 from the Hog1 cascade that regulates multiple stress responses and environmental adaptation of B. bassiana and perhaps other filamentous fungi.
Abstract Purpose : Compressed Sensing Magnetic Resonance Imaging (CS-MRI) is a promising technique to accelerate dynamic cardiac MR imaging (DCMRI). For DCMRI, the CS-MRI usually exploits image signal sparsity and low-rank property to reconstruct dynamic images from the undersampled k-space data. In this paper, a novel CS algorithm is investigated to improve dynamic cardiac MR image reconstruction quality under the condition of minimizing the k-space recording. Methods : The sparse representation of 3D cardiac magnetic resonance data is implemented by synergistically integrating 3D TGV algorithm and high order singular value decomposition (HOSVD) based Tensor Decomposition, termed as k-t TGV-TD method. In the proposed method, the low rank structure of the 3D dynamic cardiac MR data is performed by the HOSVD method, and the localized image sparsity is achieved by the 3D TGV method. Moreover, the Fast Composite Splitting Algorithm (FCSA) method, combining the variable splitting with operator splitting techniques, is employed to solve the low-rank and sparse problem. Two different cardiac MR datasets (cardiac cine and cardiac perfusion MR data) are used to evaluate the performance of the proposed method. Results : Compared with the state-of-art methods, such as the k-t SLR method, 3D TGV method and HOSVD based tensor decomposition method, the proposed method can offer improved reconstruction accuracy in terms of higher signal-to-error ratio (SER). Conclusions : This work proved that the k-t TGV-TD method was an effective sparse representation way for DC-MRI, which was capable of significantly improving the reconstruction accuracy with different reduction factor.
The ability to simulate vegetation dynamics and their feedback with nutrient cycling to affect ecosystem productivity underpins our prediction of the land carbon sink under climate change. Predictive models are now capable of simulating complex ecosystem processes, including the recent advancement in simulating vegetation dynamics and ecosystem phosphorus cycling, but there is a general lack of empirical evidence to form a systematic evaluation of the model predictions, especially how functional diversity affect ecosystem nutrient cycling and its consequence for productivity. Here, we developed a dataset based on 9 permanent plots (20 x 20 m) along an elevation gradient (300 – 1200m a.s.l.) in a subtropical forested mountain in eastern China. We measured vegetation growth, estimated forest structure and species composition, and compiled ecosystem-scale carbon (C), nitrogen (N) and phosphorus (P) budgets based on concentration, pool and flux data collected from dominant canopy trees, understorey herbaceous plants, and soil organic and inorganic components in these forested plots. Our aims are three-fold: 1) to understand how C, N and P are distributed along the plant-microbe-soil continuum; 2) to disentangle how different growth and nutrient use strategies of plant and soil microbes affect ecosystem productivity and regulate the rate nutrient cycling; and 3) to benchmark predictive models in simulating ecosystem vegetation dynamics and their interaction with C, N, and P cycle processes. Our research will contribute towards better understanding of the functional diversity and productivity relationship, and will contribute towards an improved predictive capacity to simulate vegetation dynamics and the land carbon sink under climate change.
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