Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism

Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone.     

Solute complexation degree with human serum albumin: biochromatographic approach

A mathematical model was developed for the study of the D,L-dansylamino acid retention mechanism in reversed-phase liquid chromatography using a C18 column as a stationary phase and human serum albumin (HSA) as an eluent modifier. The solute retention factor is dependent on the HSA concentration in the eluent as well as the binding constant of the guest-HSA complex. A determination of the degree of complexation n(c) (the percent of the complexed guest) could be carried out. Different Van 't Hoff plot shapes of the degree of complexation were observed with different eluent pH, confirming a change in the solute complexation mechanism for physiological pH (between 7-7.5). Enthalpy-entropy compensation was also analysed in relation to this mathematical model to confirm the solute complexation behavior with HSA. These results finally confirmed that at physiological pH and temperature (approximately 35 degrees C) values the HSA was in a favorable structural conformation for its binding with a great majority of drugs.     

中国三种常见蒿属植物潜在地理分布及其主导气候因子

裂叶蒿(Artemisia tanacetifolia)、大籽蒿(Artemisia sieversiana)和艾(Artemisia argyi)是我国常见的蒿属(Artemisia)植物,其分布区域遍布全国.本文利用MaxEnt模型预测3种蒿属植物在当前气候条件以及未来两种气候情景下的潜在分布区.采用受试者工作特征...     

scGET: Predicting Cell Fate Transition During Early Embryonic Development by Single-cell Graph Entropy

During early embryonic development, cell fate commitment represents a critical transition or"tipping point"of embryonic differentiation, at which there is a drastic and qualitative shift of the cell populations. In this study, we presented a computational approach, scGET, to explore the gene–gene associations based on single-cell RNA sequencing (scRNA-seq) data for critical transition prediction. Specifically, by transforming the gene expression data to the local network entropy, the single-cell graph entropy (SGE) value quantitatively characterizes the stability and criticality of gene regu-latory networks among cell populations and thus can be employed to detect the critical signal of cell fate or lineage commitment at the single-cell level. Being applied to five scRNA-seq datasets of embryonic differentiation, scGET accurately predicts all the impending cell fate transitions. After identifying the"dark genes"that are non-differentially expressed genes but sensitive to the SGE value, the underlying signaling mechanisms were revealed, suggesting that the synergy of dark genes and their downstream targets may play a key role in various cell development processes. The application in all five datasets demonstrates the effectiveness of scGET in analyzing scRNA-seq data from a network perspective and its potential to track the dynamics of cell differentiation. The source code of scGET is accessible at https://github.com/zhongjiayuna/scGET_Project.     

气候变化背景下基于MaxEnt模型的刺梨潜在适生区分布预测

为阐明气候变化背景下刺梨(Rosa roxburghii)在中国的潜在适生区分布,该研究基于刺梨的自然分布数据及当代(1960～1990)、未来(21世纪50年代及70年代)气候因子数据,采用最大熵(MaxEnt)模型模拟了当前和未来气候情景下刺梨在中国的潜在适生区,并确定影响其地理分布的主要气候因子.结果表明:(1)...     

On the properties and sequence context of structurally ambivalent fragments in proteins

The goal of this work is to characterize structurally ambivalent fragments in proteins. We have searched the Protein Data Bank and identified all structurally ambivalent peptides (SAPs) of length five or greater that exist in two different backbone conformations. The SAPs were classified in five distinct categories based on their structure. We propose a novel index that provides a quantitative measure of conformational variability of a sequence fragment. It measures the context-dependent width of the distribution of (phi,xi) dihedral angles associated with each amino acid type. This index was used to analyze the local structural propensity of both SAPs and the sequence fragments contiguous to them. We also analyzed type-specific amino acid composition, solvent accessibility, and overall structural properties of SAPs and their sequence context. We show that each type of SAP has an unusual, type-specific amino acid composition and, as a result, simultaneous intrinsic preferences for two distinct types of backbone conformation. All types of SAPs have lower sequence complexity than average. Fragments that adopt helical conformation in one protein and sheet conformation in another have the lowest sequence complexity and are sampled from a relatively limited repertoire of possible residue combinations. A statistically significant difference between two distinct conformations of the same SAP is observed not only in the overall structural properties of proteins harboring the SAP but also in the properties of its flanking regions and in the pattern of solvent accessibility. These results have implications for protein design and structure prediction.     

基于灰熵关联的平均住院日影响因素研究

目的:分析医疗指标与平均住院日的关联程度,为医院有效缩短平均住院日提供参考依据。方法:建立基于灰熵优化的加权灰色关联度模型,对影响平均住院日的医疗指标进行重要程度的分析。结果:根据关联程度分析,可知影响平均住院日的医疗指标重要程度依次为开放床位数、床位周转次数、治疗有效率、床位使用率、年门诊量、住院手术人次和出院人数。结论:基于灰熵优化的加权灰色关联分析方法可以有效分析医疗指标对平均住院日的影响程度,提高医疗服务质量。     

A common garden experiment with Porphyra umbilicalis (Rhodophyta) evaluates methods to study spatial differences in the macroalgal microbiome

While macroalgal microbiomes are the focus of many recent studies, there is little information about microbial spatial diversity across the thallus. Reliance on field material makes it difficult to discern whether recovered microbiomes belong to the host or its epiphytes, and technical comparisons of macroalgal samples for microbial studies are needed. Here, we use a common garden approach that avoids the problem of epiphytes, particularly at holdfasts, to examine the microbiome of Porphyra umbilicalis (strain Pum1). We used the V6 hypervariable region of the 16S rDNA with Illumina HiSeq sequencing and developed PNA clamps to block recovery of organelle V6 sequences. The common garden approach allowed us to determine differences in the microbiome at the holdfast versus blade margin. We found a notable increase in the relative abundance of Planctomycetes and Alphaproteobacteria at the holdfast, particularly of the possible symbiont Sulfitobacter sp. Nonadjacent 1.5 cm² samples of blade margin had microbiomes that were not statistically different. The most abundant phylum in the overall microbiome was Proteobacteria, followed by Bacteroidetes. Because phycologists often work in remote sites, we compared three stabilization and preparation techniques and found silica gel desiccation/bead‐beating and flash‐freezing/lyophilization/bead‐beating to be interchangeable. Core taxa (≥0.1% of sequences) across treatments were similar and accounted for ≥95% of all sequences. Finally, statistical conclusions for all comparisons were the same, regardless of which microbial community analysis tool was used: mothur or minimum entropy decomposition.     

单一景观空间分布指数及其适用性评价

为描述单一景观的空间分布离散性和广度特征,引入基于香农熵的空间分布指数(MSHDI,Modified Shannon's Distribution Index),利用河南省中南部地区1990、2001和2007年3期TM/ETM+遥感影像,进行了MSHDI与经典景观指数的比较,并分析了MSHDI与面积指数(PLAND,Percentage of Landscape)在多网格尺度下的相关关系。结果表明:(1)MSHDI在描述单一景观的空间分布广度和离散程度特征方面具有较好的适用性。MSHDI能适应不同制图综合程度的影响,并能反映出景观斑块边缘的细微差别。(2)通过分析MSHDI与PLAND之间相关系数的大小和变化程度可以分别验证MSHDI的表征性和稳定性。(3)MSHDI适用于基底和散布状景观,两种指数之间有显著的正相关性(农用地=0.939,=0.000;城市建设=0.877,=0.004;工矿仓储=0.870,=0.002;自然绿地=0.966,=0.001),且随网格粒度变化不大(农用地r=0.921±0.054;城市建设r=0.867±0.107;工矿仓储r=0.883±0.052;自然绿地r=0.964±0.024);而对网状景观则缺乏稳定性。