Five genes as a novel signature for predicting the prognosis of patients with laryngeal cancer

In this study, we purpose to investigate a novel five-gene signature for predicting the prognosis of patients with laryngeal cancer. The laryngeal cancer datasets were obtained from The Cancer Genome Atlas (TCGA). Both univariate and multivariate Cox regression analysis was applied to screening for prognostic differential expressed genes (DEGs), and a novel gene signature was obtained. The performance of this Cox regression model was tested by receiver operating characteristic (ROC) curves and area under the curve (AUC). Further survival analysis for each of the five genes was carried out through the Kaplan-Meier curve and Log-rank test. Totally, 622 DEGs were screened from the TCGA datasets in this study. We construct a five-gene signature through Cox survival analysis. Patients were divided into low- and high-risk groups depending on the median risk score, and a significant difference of the 5-year overall survival was found between these two groups (P < .05). ROC curves verified that this five-gene signature had good performance to predict the prognosis of laryngeal cancer (AUC = 0.862, P < .05). In conclusion, the five-gene signature consist of EMP1, HOXB9, DPY19L2P1, MMP1, and KLHDC7B might be applied as an independent prognosis predictor of laryngeal cancer.     

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse-phase protein arrays–based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.     

基于GTWR模型的浙江省海岸带三维生态足迹动态变化及其影响因素

厘清海岸带自然资本存量消耗和自然资本流量占用情况及其影响因素,能有效缓解海岸带社会经济发展与自然资源、生态环境之间的矛盾,促进区域协调可持续发展。本研究基于二维和三维生态足迹评价模型,分析浙江省海岸带2006—2016年生态足迹时空变化特征,基于足迹深度和足迹广度探究了区域自然资本存量和资本流量占用情况,并利用时空地理加权模型分析其影响因素的时空异质性。结果表明: 研究期间,浙江省海岸带生态危机加深,人均生态赤字平均值为3.5 hm²·cap^-1,人均生态赤字上升了15.5%,其中,能源消耗账户对人均生态足迹的贡献率大于生物资源账户;各县区人均生态足迹呈增长趋势,且空间分异显著。浙江省海岸带以消耗自然资本存量为主,且对自然资本流量更新起到较大的抑制作用;2016年,自然资本存量的消耗量是资本流量占有量的14.87倍。城市规模和经济发展水平、人民收入水平对浙江省海岸带各县区生态足迹以正向促进作用为主,渔业生产对生态足迹为负向影响,并有向正向影响作用转换的趋势,3个影响因子的影响机制时空分异性显著。     

Response of Chestnut Flowering in Beijing to Photosynthetically Active Radiation Variation and Change in Recent Fifty Years

Climate warming has affected plant phenology throughout the world, but few studies have evaluated plant phenology response to other climate factors (eg. photosynthetically active radiation PAR). In particular, the response of fruit flowering to PAR variation has not been explored yet. Long term (1963-2008) of chestnut (Castanea mollissima Blume) first flowering dates from Beijing, China were related with daily PAR for the 12 months, using Partial Least Squares (PLS) regression analysis. Two relevant phases were identified, during which mean PAR, temperature, and relative humidity (RH) were correlated with flowering dates, respectively. PAR during the both relevant periods decreased significantly in Beijing over the past 50 years. Reduced PAR during 24 September 5 February showed an advance impact on chestnut flowering, and could explain 12% of advance trend in flowering timing. Deceased PAR during 6 February 31 May had a delayed effect on tree flowering, but it was not significant enough to reject the null hypothesis of no impact over time. Advanced flowering of chestnut was mainly determined by increasing temperature between 6 February and 31 May which could explain 41% of flowering trend. Relative humidity variation during this period played secondly important role on tree flowering. Considering the interaction among these three climate factors, the impacts of PAR and RH on flowering timing could partially be attributed to the effects of temperature variation.     

Productivity,obesity, and human capital: Panel data evidence

The consequences of obesity for adults and children are well documented in the extant literature. We use panel data of 105 countries from 1990 to 2019 to estimate the effect of obesity on economic performance. We predict obesity using lagged values of child obesity as instruments. Predicted obesity has a negative and significant effect on productivity. This effect is independent of the effect of human capital and other macroeconomic determinants of economic performance. There is only weak evidence that this effect operates through the deterioration of human capital formation caused by childhood obesity.     

Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls

Despite the long‐standing interest in nonstationarity of both phenotypic evolution and diversification rates, only recently have methods been developed to study this property. Here, we propose a methodological expansion of the phylogenetic signal‐representation (PSR) curve based on phylogenetic eigenvectors to test for nonstationarity. The PSR curve is built by plotting the coefficients of determination R² from phylogenetic eigenvector regression (PVR) models increasing the number of phylogenetic eigenvectors against the accumulated eigenvalues. The PSR curve is linear under a stationary model of trait evolution (i.e. the Brownian motion model). Here we describe the distribution of shifts in the models R² and used a randomization procedure to compare observed and simulated shifts along the PSR curve, which allowed detecting nonstationarity in trait evolution. As an applied example, we show that the main evolutionary pattern of variation in the theropod dinosaur skull was nonstationary, with a significant shift in evolutionary rates in derived oviraptorosaurs, an aberrant group of mostly toothless, crested, birdlike theropods. This result is also supported by a recently proposed Bayesian‐based method (AUTEUR). A significant deviation between Ceratosaurus and Limusaurus terminal branches was also detected. We purport that our new approach is a valuable tool for evolutionary biologists, owing to its simplicity, flexibility and comprehensiveness.     

Spatial and temporal variation in harvest probabilities for American black duck

Assessing spatial variation in waterfowl harvest probabilities from banding data is challenging because reporting and recovery probabilities have distinct spatial patterns that covary temporally with harvesting regulations, hunter effort, and reporting methods. We analyzed direct band recovery data from American black ducks banded on the Canadian breeding grounds from 1970 through 2010. Data were registered to a 1‐degree grid and analyzed using hierarchical logistic regression models with spatially correlated errors to estimate the annual probabilities of band recovery and the proportion of individuals recovered in Canada. Probability of harvest was estimated from these values, in combination with independent estimates of reporting probabilities in Canada and the USA. Model covariates included estimates of hunting effort and factors for harvest regulation and band reporting methods. Both the band recovery processes and the proportion of individuals recovered in Canada had significant spatial structure. Recovery probabilities were highest in southern Ontario, along the Saint Lawrence River in Quebec, and in Nova Scotia. Black ducks breeding in Nova Scotia and southern Quebec were harvested predominantly in Canada. Recovery probabilities for juveniles were correlated with hunter effort, while the adult recoveries were weakly correlated with the implementation of stricter harvest regulations in the early 1980s. Mean harvest probability decreased in the northern portion of the survey area but remained stable or even increased in the south. Harvest probabilities for juveniles in 2010 exceeded 20% in southern Quebec and the Atlantic provinces. Our results demonstrate fine‐scale variation in harvest probabilities for black duck on the Canadian breeding ground. In particular, harvest probabilities should be closely monitored along the Saint Lawrence River system and in the Atlantic provinces to avoid overexploitation.     

嘉陵江中游长嘴剑鸻冬季觅食地选择

2009年12月至2010年2月,在嘉陵江中游采用样方法研究长嘴剑鸻Charadriusplacidus冬季觅食地选择。通过Mann-Whitney检验,发现基质类型、土壤动物生物量、裸地面积比例、距明水距离和坡度等变量在长嘴剑鸻的觅食地样方(n=62)和对照样方(n=62)间存在极显著性差异(Mann-Whitney检验,P<0.01)。对存在显著性差异的变量进行逻辑斯谛回归分析表明,裸地面积比例对长嘴剑鸻觅食地选择的影响最大,然后依次是坡度和土壤动物生物量。此外,对比渠化江段和自然江段长嘴剑鸻觅食地样方的结果表明,二者在距人为干扰距离和基质类型两个变量间存在显著性差异(Mann-Whitney检验,P<0.05),这在一定程度上反映了长嘴剑鸻对渠化江段的部分适应。总之,长嘴剑鸻偏好在食物丰富、坡度平缓的近水源裸露鹅卵石滩觅食。因此,加强沿江滩涂的保护对长嘴剑鸻有着重要意义。     

Mean difference in live-weight per incremental difference in body condition score estimated in multiple sheep breeds and crossbreds

Body condition score (BCS) is a subjective assessment of the proportion of body fat an animal possesses and is independent of frame size. There is a growing awareness of the importance of mature animal live-weight given its contribution to the overall costs of production of a sector. Because of the known relationship between BCS and live-weight, strategies to reduce live-weight could contribute to the favouring of animals with lesser body condition. The objective of the present study was to estimate the average difference in live-weight per incremental change in BCS, measured subjectively on a scale of 1 to 5. The data used consisted of 19 033 BCS and live-weight observations recorded on the same day from 7556 ewes on commercial and research flocks; the breeds represented included purebred Belclare (540 ewes), Charollais (1484 ewes), Suffolk (885 ewes), Texel (1695 ewes), Vendeen (140 ewes), as well as, crossbreds (2812 ewes). All associations were quantified using linear mixed models with the dependent variable of live-weight; ewe parity was included as a random effect. The independent variables were BCS, breed (n=6), stage of the inter-lambing interval (n=6; pregnancy, lambing, pre-weaning, at weaning, post-weaning and mating) and parity (1, 2, 3, 4 and 5+). In addition, two-way interactions were used to investigate whether the association between BCS and live-weight differed by parity, a period of the inter-lambing interval or breed. The association between BCS and live-weight differed by parity, by a period of the inter-lambing interval and by breed. Across all data, a one-unit difference in BCS was associated with 4.82 (SE=0.08) kg live-weight, but this differed by parity from 4.23 kg in parity 1 ewes to 5.82 kg in parity 5+ ewes. The correlation between BCS and live-weight across all data was 0.48 (0.47 when adjusted for nuisance factors in the statistical model), but this varied from 0.48 to 0.53 by parity, from 0.36 to 0.63 by stage of the inter-lambing interval and from 0.41 to 0.62 by breed. Results demonstrate that consideration should be taken of differences in BCS when comparing ewes on live-weight as differences in BCS contribute quite substantially to differences in live-weight; moreover, adjustments for differences in BCS should consider the population stratum, especially breed.