Modelling the biological invasion of Carcinus maenas (the European green crab)

This paper proposes a system of integro-difference equations to model the spread of Carcinus maenas, commonly called the European green crab, that causes severe damage to coastal ecosystems. A model with juvenile and adult classes is first studied. Here, standard theory of monotone operators for integro-difference equations can be applied and yields explicit formulas for the asymptotic spreading speeds of the juvenile and adult crabs. A second model including an infected class is considered by introducing a castrating parasite Sacculina carcini as a biological control agent. The dynamics are complicated and simulations reveal the occurrence of periodic solutions and stacked fronts. In this case, only conjectures can be made for the asymptotic spreading speeds because of the lack of mathematical theory for non-monotone operators. This paper also emphasizes the need for mathematical studies of non-monotone operators in heterogeneous environments and the existence of stacked front solutions in biological invasion models.     

A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training

Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.     

The effects of demographic stochasticity and parameter uncertainty on predicting the establishment of introduced species

Invasive species are a serious threat to biodiversity worldwide and predicting whether an introduced species will first establish and then become invasive can be useful to preserve ecosystem services. Establishment is influenced by multiple factors, such as the interactions between the introduced individuals and the resident community, and demographic and environmental stochasticity. Field observations are often incomplete or biased. This, together with an imperfect knowledge of the ecological traits of the introduced species, makes the prediction of establishment challenging. Methods that consider the combined effects of these factors on our ability to predict the establishment of an introduced species are currently lacking. We develop an inference framework to assess the combined effects of demographic stochasticity and parameter uncertainty on our ability to predict the probability of establishment following the introduction of a small number of individuals. We find that even moderate levels of demographic stochasticity influence both the probability of establishment, and, crucially, our ability to correctly predict that probability. We also find that estimation of the demographic parameters of an introduced species is fundamental to obtain precise estimates of the interaction parameters. For typical values of demographic stochasticity, the drop in our ability to predict an establishment can be 30% when having priors on the demographic parameters compared to having their accurate values. The results from our study illustrate how demographic stochasticity may bias the prediction of the probability of establishment. Our method can be applied to estimate probability of establishment of introduced species in field scenarios, where time series data and prior information on the demographic traits of the introduced species are available.     

Structural (UV) and carotenoid‐based plumage coloration – signals for parental investment?

Parental care increases parental fitness through improved offspring condition and survival but comes at a cost for the caretaker(s). To increase life‐time fitness, caring parents are, therefore, expected to adjust their reproductive investment to current environmental conditions and parental capacities. The latter is thought to be signaled via ornamental traits of the bearer. We here investigated whether pre‐ and/or posthatching investment of blue tit (Cyanistes caeruleus) parents was related to ornamental plumage traits (UV crown coloration and carotenoid‐based plumage coloration) expressed by either the individual itself (i.e. “good parent hypothesis”) or its partner (i.e. “differential allocation hypothesis”). Our results show that neither prehatching (that is clutch size and offspring begging intensity) nor posthatching parental investment (provisioning rate, offspring body condition at fledging) was related to an individual's UV crown coloration or to that of its partner. Similar observations were made for carotenoid‐based plumage coloration, except for a consistent positive relationship between offspring begging intensity and maternal carotenoid‐based plumage coloration. This sex‐specific pattern likely reflects a maternal effect mediated via maternally derived egg substances, given that the relationship persisted when offspring were cross‐fostered. This suggests that females adjust their offspring's phenotype toward own phenotype, which may facilitate in particular mother‐offspring co‐adaptation. Overall, our results contribute to the current state of evidence that structural or pigment‐based plumage coloration of blue tits are inconsistently correlated with central life‐history traits.     

Estimation of the diversity between DNA calorimetric profiles,differential melting curves and corresponding melting temperatures

The Poland–Fixman–Freire formalism was adapted for modeling of calorimetric DNA melting profiles, and applied to plasmid pBR 322 and long random sequences. We studied the influence of the difference (H_GC?H_AT) between the helix‐coil transition enthalpies of AT and GC base pairs on the calorimetric melting profile and on normalized calorimetric melting profile. A strong alteration of DNA calorimetrical profile with H_GC?H_AT was demonstrated. In contrast, there is a relatively slight change in the normalized profiles and in corresponding ordinary (optical) normalized differential melting curves (DMCs). For fixed H_GC?H_AT, the average relative deviation (S) between DMC and normalized calorimetric profile, and the difference between their melting temperatures (T_cal?T_m) are weakly dependent on peculiarities of the multipeak fine structure of DMCs. At the same time, both the deviation S and difference (T_cal?T_m) enlarge with the temperature melting range of the helix‐coil transition. It is shown that the local deviation between DMC and normalized calorimetric profile increases in regions of narrow peaks distant from the melting temperature.     

Analysis of the length distribution of amyloid fibrils by centrifugal sedimentation

The aggregation of normally soluble peptides and proteins into amyloid fibrils is a process associated with a wide range of pathological conditions, including Alzheimer's and Parkinson's diseases. It has become apparent that aggregates of different sizes possess markedly different biological effects, with aggregates of lower relative molecular weight being associated with stronger neurotoxicity. Yet, although many approaches exist to measure the total mass concentration of aggregates, the ability to probe the length distribution of growing aggregates in solution has remained more elusive. In this work, we applied a differential centrifugation technique to measure the sedimentation coefficients of amyloid fibrils produced during the aggregation process of the amyloid β (M1–42) peptide (Aβ42). The centrifugal method has the advantage of providing structural information on the fibril distribution directly in solution and affording a short analysis time with respect to alternative imaging and analytical centrifugation approaches. We show that under quiescent conditions interactions between Aβ42 fibrils lead to lateral association and to the formation of entangled clusters. By contrast, aggregation under shaking generates a population of filaments characterized by shorter lengths. The results, which have been validated by cryogenic transmission electron microscopy (cryo-TEM) analysis, highlight the important role that fibril–fibril assembly can play in the deposition of aggregation-prone peptides.     

Stability,sensitivity and uncertainty rates in the flow equations of ecological models

In previous work by the authors about dynamic system modeling, basic ecosystems concepts and their application to ecological modeling theory were formalized. Measuring how a variable effects certain processes leads to improvements in dynamic systems modelling and facilitates the author’s study of system diversity in which model sensitivity is a key theme. Initially, some variables and their numeric data are used for modeling. Predictions from the constructed models depend on these data. Generic study of sensitivity aims to show to what degree model behavior is altered by modification of some specific data. If small variations cause important modifications in the model’s global behavior then the model is very sensitive in relation to the variables used. If uncertain systems are considered, then it is important to submit the system to extreme situations and analyze its behavior. In this article, some indexes of uncertainty will be defined in order to determine the variables' influence in the case of extreme changes. This will permit analysis of the system’s sensitivity in relation to several simulations.     

基于蛋白互作网络识别非小细胞肺癌相关基因功能模块

本研究对非小细胞肺癌(non-small cell lung carcinoma,NSCLC)基因表达数据进行差异表达分析,并与蛋白质相互作用网络(PPIN)数据进行整合,进一步利用Heinz搜索算法识别NSCLC相关的基因功能模块,并对模块中的基因进行功能(GO term)和通路(KEGG)富集分析,旨在探究肺癌发病分子机制。蛋白互作网络分析得到一个包含96个基因和117个相互作用的功能模块,以及8个对NSCLC的发生和发展起到关键作用候选基因标志物。富集分析结果表明,这些基因主要富集于基因转录催化及染色质调控等生物学过程,并在基础转录因子、黏着连接、细胞周期、Wnt信号通路及HTLV-Ⅰ感染等生物学通路中发挥重要作用。本研究对非小细胞肺癌相关的基因和生物学通路进行预测,可用于肺癌的早期诊断和早期治疗,以降低肺癌死亡率。     

Differential seminal plasma proteome signatures of acute lymphoblastic leukemia survivors

With advances in therapeutic methods, there is a high survival rate among leukemia patients, of an extent more than 80%. However, chemotherapeutic drugs used to treat these patients have adverse effects on their overall health profile including fertility. The primary aim of this study was to identify differentially expressed proteins in seminal plasma of acute lymphoblastic leukemia (ALL) survivors compared to age-matched healthy controls, which can provide molecular basis of idiopathic infertility in such survivors. Differential proteome profiling was performed by 2D–differential in-gel electrophoresis, protein spots were identified by mass spectrometry and selective differentially expressed proteins (DEPs) were validated by western blotting and ELISA method. Out of eight DEPs identified, five proteins (isocitrate dehydrogenase 1, semenogelin 1, lactoferrin, prolactin-inducible protein, and human serum albumin) were upregulated and three (pepsinogen, prostate specific antigen and prostatic acid phosphatase) were downregulated. Expression profiles of these proteins are suggestive of reduction in semen quality in ALL survivors and can further be explored to determine their fertility status.