Quantifying energetic and fitness consequences of seasonal heterothermy in an Arctic ungulate

Animals have adapted behavioral and physiological strategies to conserve energy during periods of adverse conditions. Heterothermy is one such adaptation used by endotherms. While heterothermy—fluctuations in body temperature and metabolic rate—has been shown in large vertebrates, little is known of the costs and benefits of this strategy, both in terms of energy and in terms of fitness. Hence, our objective was to model the energetics of seasonal heterothermy in the largest Arctic ungulate, the muskox (Ovibos moschatus), using an individual‐based energy budget model of metabolic physiology. We found that the empirically based drop in body temperature (winter max ~−0.8°C) overwinter in adult females resulted in substantial fitness benefits in terms of reduced daily energy expenditure and body mass loss. Body mass and energy reserves were 8.98% and 14.46% greater in modeled heterotherms compared to normotherms by end of winter. Based on environmental simulations, we show that seasonal heterothermy can, to some extent, buffer the negative consequences of poor prewinter body condition or reduced winter food accessibility, leading to greater winter survival (+20%–30%) and spring energy reserves (+10%–30%), and thus increased probability of future reproductive success. These results indicate substantial adaptive short‐term benefits of seasonal heterothermy at the individual level, with potential implications for long‐term population dynamics in highly seasonal environments.     

Ecological total-factor energy efficiency of China’s energy intensive industries

This paper uses a meta-frontier slack-based DEA model to measure the ecological total-factor energy efficiency as well as the energy conservation potential of China’s four energy intensive subsectors. We incorporate both desirable and undesirable output together in the period, 2000–2013. The conclusions are: firstly, under the meta-frontier, the four subsectors of energy intensive industries have low average level of ecological total-factor energy efficiencies. They are 0.137, 0.212, 0.238, and 0.307 in the non-metallic mineral products manufacturing industry, raw chemical materials and chemical products manufacturing industry, smelting and pressing of ferrous metals industry, and smelting and pressing of non-ferrous metals industry, respectively. Secondly, the ecological energy efficiency in East China is the highest among three regions. Central China and West China are behind, but they are extremely close to each other. Thirdly, East China almost has no technology gap pertaining to energy efficiency, while Central China and West China almost have the same gap. Finally, Sichuan is considered to be the best province in West China under group frontier due to its perform in the three energy intensive subsectors. For Central and East China, no province has higher ecological energy efficiency in more than two energy intensive subsectors.     

Analysis of absorption spectra of purple bacterial reaction centers in the near infrared region by higher order derivative spectroscopy

Reaction centers (RCs) of purple bacteria are uniquely suited objects to study the mechanisms of the photosynthetic conversion of light energy into chemical energy. A recently introduced method of higher order derivative spectroscopy [I.K. Mikhailyuk, H. Lokstein, A.P. Razjivin, A method of spectral subband decomposition by simultaneous fitting the initial spectrum and a set of its derivatives, J. Biochem. Biophys. Methods 63 (2005) 10-23] was used to analyze the NIR absorption spectra of RC preparations from Rhodobacter (R.) sphaeroides strain 2R and Blastochloris (B.) viridis strain KH, containing bacteriochlorophyll (BChl) a and b, respectively. Q(y) bands of individual RC porphyrin components (BChls and bacteriopheophytins, BPheo) were identified. The results indicate that the upper exciton level P(y+) of the photo-active BChl dimer in RCs of R. sphaeroides has an absorption maximum of 810nm. The blue shift of a complex integral band at approximately 800nm upon oxidation of the RC is caused primarily by bleaching of P(y+), rather than by an electrochromic shift of the absorption band(s) of the monomeric BChls. Likewise, the disappearance of a band peaking at 842nm upon oxidation of RCs from B. viridis indicates that this band has to be assigned to P(y+). A blue shift of an absorption band at approximately 830nm upon oxidation of RCs of B. viridis is also essentially caused by the disappearance of P(y+), rather than by an electrochromic shift of the absorption bands of monomeric BChls. Absorption maxima of the monomeric BChls, B(B) and B(A) are at 802 and 797nm, respectively, in RCs of R. sphaeroides at room temperature. BPheo co-factors H(B) and H(A) peak at 748 and 758nm, respectively, at room temperature. For B. viridis RCs the spectral positions of H(B) and H(A) were found to be 796 and 816nm, respectively, at room temperature.     

Accuracy of side-chain prediction upon near-native protein backbones generated by ab initio folding methods

The ab initio folding problem can be divided into two sequential tasks of approximately equal computational complexity: the generation of native-like backbone folds and the positioning of side chains upon these backbones. The prediction of side-chain conformation in this context is challenging, because at best only the near-native global fold of the protein is known. To test the effect of displacements in the protein backbones on side-chain prediction for folds generated ab initio, sets of near-native backbones (≤ 4 Å Cα RMS error) for four small proteins were generated by two methods. The steric environment surrounding each residue was probed by placing the side chains in the native conformation on each of these decoys, followed by torsion-space optimization to remove steric clashes on a rigid backbone. We observe that on average 40% of the χ1 angles were displaced by 40° or more, effectively setting the limits in accuracy for side-chain modeling under these conditions. Three different algorithms were subsequently used for prediction of side-chain conformation. The average prediction accuracy for the three methods was remarkably similar: 49% to 51% of the χ1 angles were predicted correctly overall (33% to 36% of the χ1+2 angles). Interestingly, when the inter-side-chain interactions were disregarded, the mean accuracy increased. A consensus approach is described, in which side-chain conformations are defined based on the most frequently predicted χ angles for a given method upon each set of near-native backbones. We find that consensus modeling, which de facto includes backbone flexibility, improves side-chain prediction: χ1 accuracy improved to 51–54% (36–42% of χ1+2). Implications of a consensus method for ab initio protein structure prediction are discussed. Proteins 33:204–217, 1998. © 1998 Wiley-Liss, Inc.     

Multifaceted applications of nanomaterials in cell engineering and therapy

Nanomaterials with superior physiochemical properties have been rapidly developed and integrated in every aspect of cell engineering and therapy for translating their great promise to clinical success. Here we demonstrate the multifaceted roles played by innovatively-designed nanomaterials in addressing key challenges in cell engineering and therapy such as cell isolation from heterogeneous cell population, cell instruction in vitro to enable desired functionalities, and targeted cell delivery to therapeutic sites for prompting tissue repair. The emerging trends in this interdisciplinary and dynamic field are also highlighted, where the nanomaterial-engineered cells constitute the basis for establishing in vitro disease model; and nanomaterial-based in situ cell engineering are accomplished directly within the native tissue in vivo. We will witness the increasing importance of nanomaterials in revolutionizing the concept and toolset of cell engineering and therapy which will enrich our scientific understanding of diseases and ultimately fulfill the therapeutic demand in clinical medicine.     

A quantitative structure-activity relationship study for structurally diverse HIV-1 protease inhibitors: contribution of conformational flexibility to inhibitory activity

In this study, we investigated by linear regression model the SAR data of the 15 HIV-1 protease inhibitors possessing structurally diverse scaffolds. First, a regression model was developed only using the enzyme-inhibitor interaction energy as a term of the model, but did not provide a good correlation with the inhibitory activity (R² = 0.580 and Q² = 0.500). Then, we focused on the conformational flexibility of the inhibitors which may represent the diversity of the inhibitors, and added two conformational parameters into the model, respectively: the number of rotatable bonds of ligands (ΔSrot) and the distortion energy of ligands (ΔElig). The regression model by adding ΔElig successfully improved the quality of the model (R² = 0.771 and Q² = 0.713) while the model with ΔSrot was unsuccessful. The prediction for a training inhibitor by the ΔElig model also showed good agreement with experimental activity. These results suggest that the conformational flexibility of HIV-1 protease inhibitors directly contributes to the enzyme inhibition.     

锰矿修复区植物生态系统自由能与化学势分析

基于热力学理论建立了生态系统Gibbs自由能方程,用以计算湘潭锰矿生态修复区植被系统的自由能(G)和物种化学势(μ)。生态修复区(及对照区)以泡桐(Paulownia fortunei)和栾树(Koelreuteria bipinnata)作为建群植物,总面积为4 hm~2,修复区泡桐和栾树的根际施用了含有自试验点废弃矿渣中筛选出的耐性菌株的有机菌肥,目的是为植物生长提供必要养分和降低根际土壤重金属毒性,对照区泡桐和栾树的根际施用了等量的化肥。泡桐和栾树种植后5 a期间,修复区与对照区均自然萌发生长了许多本土植物种类。试验结果表明,修复区植物种类数达到48,为对照区的3.7倍;修复区的总生物量、锰吸收量分别达到23324 kg/hm~2和4280 g/hm~2,为对照区对应值的20.6和2.6倍;修复区系统自由能G远远大于对照区的值,说明有机菌肥具有显著的改良污染土壤根际环境的效果。修复区和对照区植物种类之间的化学势μ均存在显著差异(P0.001),μ值差异范围分别为-3.79—6.76和-3.42—3.59,该一差异反映不同物种适应和修复锰污染环境的能力。G和μ值包含了生态系统生产力、生物多样性,植物种类生长势、重金属富集能力、生态学行为等综合信息,能反映生态系统与立地环境的关系和修复植物的生态学特性,可作为重金属污染区植被修复效果评价和修复植物筛选的重要指标。     

Kinetics and thermodynamics of a novel endoglucanase (CMCase) from <Emphasis Type="Italic">Gymnoascella </Emphasis><Emphasis Type="Italic">citrina</Emphasis> produced under solid-state condition

Gymnoascella citrina produced two isoforms of endoglucanases (CMCase-I and -capital I, Ukrainiancapital I, Ukrainian) under solid-state condition. Purified CMCase-I was novel because it was apparently holoenzyme in nature. The enzyme was monomeric as its native and subunit mass were almost the same, i.e., 43 and 42 kDa, respectively. Ea for carboxymethylcellulose (CMC) hydrolysis was 36.2 kJ mol(-1). The enzyme was stable over a pH range of 3.5-6.5, while temperature optimum was 55 degrees C. Vmax, Km and k (cat )for CMC hydrolysis were 39 U mg(-1) protein, 6.25 mg CMC mL(-1) and 27.5 s(-1), respectively. The pKa1 and pKa2 of ionizable groups of active site were 2.8 and 7.4, respectively. Thermodynamic parameters for CMC hydrolysis were as follows: DeltaH*=33.5 kJ mol(-1), DeltaG*=70.42 kJ mol(-1) and DeltaS*=-114.37 J mol(-1) K(-1). The removal of metals resulted into complete loss of enzymatic activity and was completely recovered in the presence of 1 mM Mn2+, whereas inhibition initiated at 5 mM. The other metals like Ca2+, Zn2+ and K1+ showed no inhibition up to 7 mM, Co2+ completely inhibited the activity, while Mg2+ could not recover the initial activity up to 7 mM. So we are reporting for the first time, kinetics and thermodynamics of CMCase-Iota from G. citrina.     

Functional genomics of brain aging and Alzheimer's disease: focus on selective neuronal vulnerability

Pivotal brain functions, such as neurotransmission, cognition, and memory, decline with advancing age and, especially, in neurodegenerative conditions associated with aging, such as Alzheimer's disease (AD). Yet, deterioration in structure and function of the nervous system during aging or in AD is not uniform throughout the brain. Selective neuronal vulnerability (SNV) is a general but sometimes overlooked characteristic of brain aging and AD. There is little known at the molecular level to account for the phenomenon of SNV. Functional genomic analyses, through unbiased whole genome expression studies, could lead to new insights into a complex process such as SNV. Genomic data generated using both human brain tissue and brains from animal models of aging and AD were analyzed in this review. Convergent trends that have emerged from these data sets were considered in identifying possible molecular and cellular pathways involved in SNV. It appears that during normal brain aging and in AD, neurons vulnerable to injury or cell death are characterized by significant decreases in the expression of genes related to mitochondrial metabolism and energy production. In AD, vulnerable neurons also exhibit down-regulation of genes related to synaptic neurotransmission and vesicular transport, cytoskeletal structure and function, and neurotrophic factor activity. A prominent category of genes that are up-regulated in AD are those related to inflammatory response and some components of calcium signaling. These genomic differences between sensitive and resistant neurons can now be used to explore the molecular underpinnings of previously suggested mechanisms of cell injury in aging and AD.