Study and modeling of fluctuating dissolved oxygen concentration impact on Corynebacterium glutamicum growth in a scale-down bioreactor

In this study, the impact of dissolved oxygen concentrations oscillations on Corynebacterium glutamicum 2262 ΔldhA growth was studied experimentally and modeled. Aiming at this, a dedicated two-compartment scale down set-up composed of two interconnected aerobic/anaerobic stirred tank bioreactors was used. The mean residence time of bacteria in each compartment was modified by adapting circulation rates and culture volumes in each bioreactor and the resulting temporal ratio of aeration was calculated. The five growth kinetics were then modeled using an original kinetic model coupling Monod growth modeling and the Residence Time Distributions. Our study showed that the microbial growth rate and macroscopic yields were clearly linked to the temporal ratio of aeration, allowing the definition of simple but robust law for process scale-up purpose. It was also revealed that the model proposed precisely agreed with the experimental growth data, whatever the fractions of aeration time imposed experimentally.     

珊瑚礁生态系统模型研究现状及热点分析

以Web of Science数据库中的Web of Science ~(TM)核心合集和中国期刊全文数据库为数据源,对2018年10月前国内外发表的珊瑚礁生态系统模型研究相关文献进行计量分析,评估该领域的研究现状及热点。研究表明:国外珊瑚礁生态系统模型研究起始于1974年,相关文献的发文量整体呈大幅度增长趋势;国内研究于1997年起步,发文量增长较缓慢,近三年显著增加。高频关键词统计分析可以看出,国外对于珊瑚礁中生活的各种生物及其生态分布研究较为广泛,生态系统的生物群落多样性是该领域的研究热点,关于珊瑚礁生态系统风险、威胁、胁迫和修复的模型研究近几年有所起色,在今后一段时间内将是该领域的主要研究趋势。国内相关研究局限于珊瑚礁地质环境与波浪传播等方面,应在扩大研究范围的同时,将重点放在珊瑚礁生态系统退化诊断与修复的探究上。     

Temperature and precipitation at migratory grounds influence demographic trends of an Arctic‐breeding bird

Anthropogenic climate disruption, including temperature and precipitation regime shifts, has been linked to animal population declines since the mid‐20th century. However, some species, such as Arctic‐breeding geese, have thrived during this period. An increased understanding of how climate disruption might link to demographic rates in thriving species is an important perspective in quantifying the impact of anthropogenic climate disruption on the global state of nature. The Greenland barnacle goose (Branta leucopsis) population has increased tenfold in abundance since the mid‐20th century. A concurrent weather regime shift towards warmer, wetter conditions occurred throughout its range in Greenland (breeding), Ireland and Scotland (wintering) and Iceland (spring and autumn staging). The aim of this study was to determine the relationship between weather and demographic rates of Greenland barnacle geese to discern the role of climate shifts in the population trend. We quantified the relationship between temperature and precipitation and Greenland barnacle goose survival and productivity over a 50 year period from 1968 to 2018. We detected significant positive relationships between warmer, wetter conditions on the Icelandic spring staging grounds and survival. We also detected contrasting relationships between warmer, wetter conditions during autumn staging and survival and productivity, with warm, dry conditions being the most favourable for productivity. Survival increased in the latter part of the study period, supporting the possibility that spring weather regime shifts contributed to the increasing population trend. This may be related to improved forage resources, as warming air temperatures have been shown to improve survival rates in several other Arctic and northern terrestrial herbivorous species through indirect bottom‐up effects on forage availability.     

A population‐averaged approach to diagnostic test meta‐analysis

The meta‐analysis of diagnostic accuracy studies is often of interest in screening programs for many diseases. The typical summary statistics for studies chosen for a diagnostic accuracy meta‐analysis are often two dimensional: sensitivities and specificities. The common statistical analysis approach for the meta‐analysis of diagnostic studies is based on the bivariate generalized linear‐mixed model (BGLMM), which has study‐specific interpretations. In this article, we present a population‐averaged (PA) model using generalized estimating equations (GEE) for making inference on mean specificity and sensitivity of a diagnostic test in the population represented by the meta‐analytic studies. We also derive the marginalized counterparts of the regression parameters from the BGLMM. We illustrate the proposed PA approach through two dataset examples and compare performance of estimators of the marginal regression parameters from the PA model with those of the marginalized regression parameters from the BGLMM through Monte Carlo simulation studies. Overall, both marginalized BGLMM and GEE with sandwich standard errors maintained nominal 95% confidence interval coverage levels for mean specificity and mean sensitivity in meta‐analysis of 25 of more studies even under misspecification of the covariance structure of the bivariate positive test counts for diseased and nondiseased subjects.     

Analysis of cause of death: Competing risks or progressive illness‐death model?

The analysis of cause of death is increasingly becoming a topic in oncology. It is usually distinguished between disease‐related and disease‐unrelated death. A frequently used approach is to define death as disease‐related when a progression to advanced phases has occurred before, otherwise as disease‐unrelated. The data are often analyzed as competing risks, while a progressive illness‐death model might in fact describe the situation more precisely. In this study, we investigated under which circumstances this misspecification leads to biased estimations of the state occupation probabilities. We simulated data according to the progressive illness‐death model in various settings, analyzed them with a competing risks model and with a progressive illness‐death model and compared them to the true state occupation probabilities. Censoring was either added independently of the status or based on the patients' status. The simulations showed that the censoring mechanism was decisive for the bias while neither the progression hazard nor the Markov property was important. Further, we found a slightly increased standard deviation for the competing risk estimator when censoring was independent of the patients' status. For illustration, both methods were applied to two practical examples of chronic myeloid leukemia (CML): one randomized controlled trial and one registry data set. While in the first case both estimators yielded almost identical results, in the latter case, visible differences were found between both methods.     

Paroxysmal and cognitive phenotypes in Prrt2 mutant mice

Mutations in proline‐rich transmembrane protein 2 (PRRT2) cause a range of episodic disorders that include paroxysmal kinesigenic dyskinesia and benign familial infantile epilepsy. Mutations are generally loss of function and include the c649dupC frameshifting mutation that is present in around 80% of affected individuals. To investigate how Prrt2 loss of function mutations causes disease, we performed a phenotypic investigation of a transgenic Prrt2 knockout (Prrt2 KO) mouse. We observed spontaneous paroxysmal episodes with behavioural features of both seizure and movement disorders, as well as unexplained deaths in KO and HET animals. KO mice showed spatial learning deficits in the Morris water maze, as well as gait abnormalities in the quantitative Digigait analysis; both of which may be representative of the more severe phenotypes experienced by homozygous patients. These findings extend the described phenotypes of Prrt2 mutant mice, further confirming their utility for in vivo investigation of the role of Prrt2 mutations in episodic diseases.     

Mean growth rate when rare is not a reliable metric for persistence of species

The coexistence of many species within ecological communities poses a long‐standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, , is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on and show that it fails to capture the effect of temporal random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in , since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as increases.     

Influence of climate change and postdelisting management on long‐term population viability of the conservation‐reliant Kirtland's Warbler

Rapid global climate change is resulting in novel abiotic and biotic conditions and interactions. Identifying management strategies that maximize probability of long‐term persistence requires an understanding of the vulnerability of species to environmental changes. We sought to quantify the vulnerability of Kirtland's Warbler (Setophaga kirtlandii), a rare Neotropical migratory songbird that breeds almost exclusively in the Lower Peninsula of Michigan and winters in the Bahamian Archipelago, to projected environmental changes on the breeding and wintering grounds. We developed a population‐level simulation model that incorporates the influence of annual environmental conditions on the breeding and wintering grounds, and parameterized the model using empirical relationships. We simulated independent and additive effects of reduced breeding grounds habitat quantity and quality, and wintering grounds habitat quality, on population viability. Our results indicated the Kirtland's Warbler population is stable under current environmental and management conditions. Reduced breeding grounds habitat quantity resulted in reductions of the stable population size, but did not cause extinction under the scenarios we examined. In contrast, projected large reductions in wintering grounds precipitation caused the population to decline, with risk of extinction magnified when breeding habitat quantity or quality also decreased. Our study indicates that probability of long‐term persistence for Kirtland's Warbler will depend on climate change impacts to wintering grounds habitat quality and contributes to the growing literature documenting the importance of considering the full annual cycle for understanding population dynamics of migratory species.     

离散广义Logistic模型的稳定性和浑沌现象

文[1]提出了单种生长的连续性文广义Logistic dx/dt=γx({K-x}/(K+px))其中γ>ο为种群的内禀生长率,K>0为环境容纳量,ν>-1表示种群对环境(包括营