The modified Q-cycle: A look back at its development and forward to a functional model

On looking back at a lifetime of research, it is interesting to see, in the light of current progress, how things came to be, and to speculate on how things might be. I am delighted in the context of the Mitchell prize to have that excuse to present this necessarily personal view of developments in areas of my interests. I have focused on the Q-cycle and a few examples showing wider ramifications, since that had been the main interest of the lab in the 20 years since structures became available, - a watershed event in determining our molecular perspective. I have reviewed the evidence for our model for the mechanism of the first electron transfer of the bifurcated reaction at the Q_o-site, which I think is compelling. In reviewing progress in understanding the second electron transfer, I have revisited some controversies to justify important conclusions which appear, from the literature, not to have been taken seriously. I hope this does not come over as nitpicking. The conclusions are important to the final section in which I develop an internally consistent mechanism for turnovers of the complex leading to a state similar to that observed in recent rapid-mix/freeze-quench experiments, reported three years ago. The final model is necessarily speculative but is open to test.     

脊髓缺血再灌注损伤动物模型的研究进展

脊髓缺血再灌注损伤(Spinal cord ischemia reperfusion injury,SCIRI)模型对研究临床上SCIRI至关重要。SCIRI动物模型旨在尽可能模拟临床脊髓损伤的病理特点。SCIRI模型因所用动物和方法不同而不同。目前国内外常用的SCIRI模型实验动物包括兔、大鼠和小鼠。大鼠因其脊髓血供和人类相似、相对廉价、繁殖力强且容易获得常常用于制作脊髓再灌注损伤模型。任何模型均有其优缺点。可靠、稳定的动物模型对研究SCIRI的发生机制及评估干预手段的效果和寻求有效的治疗方法具有非常重要的意义。该文就SCIRI动物模型研究进展进行简要综述,为研究者们选择最适合自己研究目标的动物模型提供一定的借鉴。     

Integrating plant–soil interactions into global carbon cycle models

1.  Plant–soil interactions play a central role in the biogeochemical carbon (C), nitrogen (N) and hydrological cycles. In the context of global environmental change, they are important both in modulating the impact of climate change and in regulating the feedback of greenhouse gas emissions (CO₂, CH₄ and N₂O) to the climate system.
2.  Dynamic global vegetation models (DGVMs) represent the most advanced tools available to predict the impacts of global change on terrestrial ecosystem functions and to examine their feedbacks to climate change. The accurate representation of plant–soil interactions in these models is crucial to improving predictions of the effects of climate change on a global scale.
3.  In this paper, we describe the general structure of DGVMs that use plant functional types (PFTs) classifications as a means to integrate plant–soil interactions and illustrate how models have been developed to improve the simulation of: (a) soil carbon dynamics, (b) nitrogen cycling, (c) drought impacts and (d) vegetation dynamics. For each of these, we discuss some recent advances and identify knowledge gaps.
4.  We identify three ongoing challenges, requiring collaboration between the global modelling community and process ecologists. First, the need for a critical evaluation of the representation of plant–soil processes in global models; second, the need to supply and integrate knowledge into global models; third, the testing of global model simulations against large-scale multifactor experiments and data from observatory gradients.
5.   Synthesis . This paper reviews how plant–soil interactions are represented in DGVMs that use PFTs and illustrates some model developments. We also identify areas of ecological understanding and experimentation needed to reduce uncertainty in future carbon coupled climate change predictions.     

A Generalization of the Mixture Model in the Mapping of Quantitative Trait Loci for Progeny from a Biparental Cross of Inbred Lines

The recent advent of molecular markers has created a great potential for the understanding of quantitative inheritance. In parallel to rapid developments and improvements in molecular marker technologies, biometrical models have been constructed, refined and generalized for the mapping of quantitative trait loci (QTL). However, current models present restricitions in terms of breeding designs to which they apply. In this paper, we develop an approach for the generalization of the mixture model for progeny from a single bi-parental cross of inbred lines. Detailed derivations are given for genetic designs involving populations developed by selfing, i.e., where marker genotypes are obtained from F(x) (x >=2) individuals and where phenotypes are measured on F(y) (y >=x) individuals or families. Extensions to designs involving doubled-haploids, backcross-derived individuals and random matings are outlined. The derivations presented here can easily be combined with current QTL mapping approaches.     

Development of bioinformatics and multi-omics analyses in organoids

Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids.     

There's more than one frog in the pond: a survey of the Amphibia and their contributions to developmental biology

The study of developmental biology has benefited greatly from the insights gained using amphibians as experimental models. Although Xenopus is currently the predominant model, much of our embryological knowledge derives from research on other amphibians. I will review some of these discoveries, made through astute choice of model organism, and I will examine the reasons behind the adoption of Xenopus as the standard for amphibian research. Additionally, I will discuss the diversity in developmental and reproductive strategies that exists within the Amphibia, and consider some of the recent advances in our understanding of the mechanisms underlying this developmental diversity.     

Exploratory path analysis with applications in ecology and evolution

In this article, I first describe some recent developments in the identification of the structure of dependencies among variables in multivariate data relevant to exploratory path analysis. I then introduce a bootstrap modification of one important method (the SGS algorithm) that is designed to improve error rates of exploratory path analysis in the small data sets that are typical of studies in ecology and evolution. Monte Carlo results indicate that this modified technique can find path models that are close to the true model even in very small data sets. The bootstrapped SGS algorithm is then applied to a previously published data set involving attributes affecting seed dispersal in St. Lucie's cherry.     

Understanding plant reproductive diversity

Flowering plants display spectacular floral diversity and a bewildering array of reproductive adaptations that promote mating, particularly outbreeding. A striking feature of this diversity is that related species often differ in pollination and mating systems, and intraspecific variation in sexual traits is not unusual, especially among herbaceous plants. This variation provides opportunities for evolutionary biologists to link micro-evolutionary processes to the macro-evolutionary patterns that are evident within lineages. Here, I provide some personal reflections on recent progress in our understanding of the ecology and evolution of plant reproductive diversity. I begin with a brief historical sketch of the major developments in this field and then focus on three of the most significant evolutionary transitions in the reproductive biology of flowering plants: the pathway from outcrossing to predominant self-fertilization, the origin of separate sexes (females and males) from hermaphroditism and the shift from animal pollination to wind pollination. For each evolutionary transition, I consider what we have discovered and some of the problems that still remain unsolved. I conclude by discussing how new approaches might influence future research in plant reproductive biology.     

Reduction of stochastic conductance-based neuron models with time-scales separation

We introduce a method for systematically reducing the dimension of biophysically realistic neuron models with stochastic ion channels exploiting time-scales separation. Based on a combination of singular perturbation methods for kinetic Markov schemes with some recent mathematical developments of the averaging method, the techniques are general and applicable to a large class of models. As an example, we derive and analyze reductions of different stochastic versions of the Hodgkin Huxley (HH) model, leading to distinct reduced models. The bifurcation analysis of one of the reduced models with the number of channels as a parameter provides new insights into some features of noisy discharge patterns, such as the bimodality of interspike intervals distribution. Our analysis of the stochastic HH model shows that, besides being a method to reduce the number of variables of neuronal models, our reduction scheme is a powerful method for gaining understanding on the impact of fluctuations due to finite size effects on the dynamics of slow fast systems. Our analysis of the reduced model reveals that decreasing the number of sodium channels in the HH model leads to a transition in the dynamics reminiscent of the Hopf bifurcation and that this transition accounts for changes in characteristics of the spike train generated by the model. Finally, we also examine the impact of these results on neuronal coding, notably, reliability of discharge times and spike latency, showing that reducing the number of channels can enhance discharge time reliability in response to weak inputs and that this phenomenon can be accounted for through the analysis of the reduced model.     

Imaging of the host/parasite interplay in cutaneous leishmaniasis

An understanding of host-parasite interplay is essential for the development of therapeutics and vaccines. Immunoparasitologists have learned a great deal from ‘conventional’ in vitro and in vivo approaches, but recent developments in imaging technologies have provided us (immunologists and parasitologists) with the ability to ask new and exciting questions about the dynamic nature of the parasite-immune system interface. These studies are providing us with new insights into the mechanisms involved in the initiation of a Leishmania infection and the consequent induction and regulation of the immune response. Here, we review some of the recent developments and discuss how these observations can be further developed to understand the immunology of cutaneous Leishmania infection in vivo.     

Shutdown decay of mRNA

Although plasmid-borne and chromosomal toxin-antitoxin (TA) operons have been known for some time, the recent identification of mRNA as the target of at least two different classes of toxins has led to a dramatic renewal of interest in these systems as mediators of stress responses. Members of the MazF/PemK family, the so-called mRNA interferases, are ribonucleases that inhibit translation by destroying cellular mRNAs under stress conditions, while the founder member of the RelE family promotes cleavage of mRNAs through the ribosome. Detailed structures of these enzymes, often in complex with their inhibitors, have provided vital clues to their mechanisms of action. The primary role and regulation of these systems has been the subject of some controversy. One model suggests they play a beneficial role by wiping the slate clean and preventing wasteful energy consumption by the translational apparatus during adaptation to stress conditions, while another favours the idea that their main function is programmed cell death. The two models might not be mutually exclusive if a side-effect of prolonged exposure to toxic RNase activity without de novo synthesis of the inhibitor were a state of dormancy for which we do not yet understand the key to recovery. In this review, I discuss the recent developments in the rapidly expanding field of what I refer to as bacterial shutdown decay.     

Resolving the kinetics of lipid,protein and peptide diffusion in membranes

Abstract

Recent developments in the understanding of molecular diffusion phenomena in membranes are reviewed. Both model bilayers and biological membranes are considered in respect of lateral diffusion, rotational diffusion and transverse diffusion (flip-flop). For model systems, particular attention is paid to recent data obtained using surface-specific techniques such as sum frequency generation vibrational spectroscopy on supported lipid bilayers, and fluorescence correlation spectroscopy on giant unilamellar vesicles, both of which have yielded new insights into the intrinsic rates of diffusion and the energetic barriers to processes such as lipid flip-flop. Advances in single-molecule and many-molecule fluorescence methodologies have enabled the observation of processes such as anomalous diffusion for some membrane species in biological membranes. These are discussed in terms of new models for the role of membrane interactions with the cytoskeleton, the effects of molecular crowding in membranes, and the formation of lipid rafts. The diffusion of peptides, proteins and lipids is considered, particularly in relation to the means by which antimicrobial peptide activity may be rationalized in terms of membrane poration and lipid flip-flop.     

On the dangers of making scientific models ontologically independent: taking Richard Levins’ warnings seriously

Levins and Lewontin have contributed significantly to our philosophical understanding of the structures, processes, and purposes of biological mathematical theorizing and modeling. Here I explore their separate and joint pleas to avoid making abstract and ideal scientific models ontologically independent by confusing or conflating our scientific models and the world. I differentiate two views of theorizing and modeling, orthodox and dialectical, in order to examine Levins and Lewontin’s, among others, advocacy of the latter view. I compare the positions of these two views with respect to four points regarding ontological assumptions: (1) the origin of ontological assumptions, (2) the relation of such assumptions to the formal models of the same theory, (3) their use in integrating and negotiating different formal models of distinct theories, and (4) their employment in explanatory activity. Dialectical is here used in both its Hegelian–Marxist sense of opposition and tension between alternative positions and in its Platonic sense of dialogue between advocates of distinct theories. I investigate three case studies, from Levins and Lewontin as well as from a recent paper of mine, that show the relevance and power of the dialectical understanding of theorizing and modeling.     

Adaptive sex allocation in birds: the complexities of linking theory and practice

We review some recent theoretical and empirical developments in the study of sex allocation in birds. The advent of reliable molecular sexing techniques has led to a sharp increase in the number of studies that report biased offspring sex ratios in birds. However, compelling evidence for adaptive sex allocation in birds is still very scant. We argue that there are two reasons for this: (i) standard sex allocation models, very helpful in understanding sex allocation of invertebrates, do not sufficiently take the complexities of bird life histories and physiology into account. Recent theoretical work might bring us a step closer to more realistic models; (ii) experimental field and laboratory studies on sex allocation in birds are scarce. Recent experimental work both in the laboratory and in the field shows that this is a promising approach.     

Multilevel selection theory and evidence: a critique of Gardner, 2015

Gardner (2015) recently developed a model of a ‘Genetical Theory of Multilevel Selection, which is a thoughtfully developed, but flawed model. The model's flaws appear to be symptomatic of common misunderstandings of the multi level selection (MLS) literature and the recent quantitative genetic literature. I use Gardner's model as a guide for highlighting how the MLS literature can address the misconceptions found in his model, and the kin selection literature in general. I discuss research on the efficacy of group selection, the roll of indirect genetic effects in affecting the response to selection and the heritability of group‐level traits. I also discuss why the Price multilevel partition should not be used to partition MLS, and why contextual analysis and, by association, direct fitness are appropriate for partitioning MLS. Finally, I discuss conceptual issues around questions concerning the level at which fitness is measured, the units of selection, and I present a brief outline of a model of selection in class‐structured populations. I argue that the results derived from the MLS research tradition can inform kin selection research and models, and provide insights that will allow researchers to avoid conceptual flaws such as those seen in the Gardner model.     

Understanding cornea epithelial stem cells and stem cell deficiency: Lessons learned using vertebrate model systems

Animal models have contributed greatly to our understanding of human diseases. Here, we focus on cornea epithelial stem cell (CESC) deficiency (commonly called limbal stem cell deficiency, LSCD). Corneal development, homeostasis and wound healing are supported by specific stem cells, that include the CESCs. Damage to or loss of these cells results in blindness and other debilitating ocular conditions. Here we describe the contributions from several vertebrate models toward understanding CESCs and LSCD treatments. These include both mammalian models, as well as two aquatic models, Zebrafish and the amphibian, Xenopus. Pioneering developments have been made using stem cell transplants to restore normal vision in patients with LSCD, but questions still remain about the basic biology of CESCs, including their precise cell lineages and behavior in the cornea. We describe various cell lineage tracing studies to follow their patterns of division, and the fates of their progeny during development, homeostasis, and wound healing. In addition, we present some preliminary results using the Xenopus model system. Ultimately, a more thorough understanding of these cornea cells will advance our knowledge of stem cell biology and lead to better cornea disease therapeutics.     

Mouse genetics in the 21st century: using gene targeting to create a cornucopia of mouse mutants possessing precise genetic modifications

Over 1500 mouse mutants have been identified, but few of the genes responsible for the defects have been identified. Recent developments in the area of gene targeting are revolutionizing the field of mouse genetics and our understanding of numerous genes, including those thought to be involved in cell proliferation and differentiation. Gene targeting was developed as a method for producing a predetermined mutation in a specific endogenous gene. Advances in the design of targeting vectors and in the use of embryonic stem cells have permitted the production of numerous mutant mice with null mutations in specific genes. These mutant mice will be critical for investigating thein vivo functions of many genes that have been cloned in recent years. This review discusses a wide range of new developments in the field of gene targeting with a focus on issues to be considered by those planning to use this new technology. It also examines some of the lessons learned from recent gene targeting studies and discusses different applications of the technology that are likely to generate scores of new animal models for a wide range of human diseases.Abbreviations ES embryonic stem - neo^r neomycin resistance gene - HSV herpes simplex virus - tk thymidine kinase gene - PCR polymerase chain reaction - LIF leukemia inhibitory factor - LTP long-term potentiation - Rb retinoblastoma gene product - CF cystic fibrosis     

The consequences of structural genomic alterations in humans: genomic disorders, genomic instability and cancer

Over the last decade or so, sophisticated technological advances in array-based genomics have firmly established the contribution of structural alterations in the human genome to a variety of complex developmental disorders, and also to diseases such as cancer. In fact, multiple 'novel' disorders have been identified as a direct consequence of these advances. Our understanding of the molecular events leading to the generation of these structural alterations is also expanding. Many of the models proposed to explain these complex rearrangements involve DNA breakage and the coordinated action of DNA replication, repair and recombination machinery. Here, and within the context of Genomic Disorders, we will briefly overview the principal models currently invoked to explain these chromosomal rearrangements, including Non-Allelic Homologous Recombination (NAHR), Fork Stalling Template Switching (FoSTeS), Microhomology Mediated Break-Induced Repair (MMBIR) and Breakage-fusion-bridge cycle (BFB). We will also discuss an unanticipated consequence of certain copy number variations (CNVs) whereby the CNVs potentially compromise fundamental processes controlling genomic stability including DNA replication and the DNA damage response. We will illustrate these using specific examples including Genomic Disorders (DiGeorge/Veleocardiofacial syndrome, HSA21 segmental aneuploidy and rec (3) syndrome) and cell-based model systems. Finally, we will review some of the recent exciting developments surrounding specific CNVs and their contribution to cancer development as well as the latest model for cancer genome rearrangement; 'chromothripsis'.     

Kidney disease models:tools to identify mechanisms and potential therapeutic targets

Acute kidney injury(AKI) and chronic kidney disease(CKD) are worldwide public health problems affecting millions of people and have rapidly increased in prevalence in recent years. Due to the multiple causes of renal failure, many animal models have been developed to advance our understanding of human nephropathy. Among these experimental models, rodents have been extensively used to enable mechanistic understanding of kidney disease induction and progression, as well as to identify potential targets for therapy. In this review, we discuss AKI models induced by surgical operation and drugs or toxins, as well as a variety of CKD models(mainly genetically modified mouse models).Results from recent and ongoing clinical trials and conceptual advances derived from animal models are also explored.     

Complexity,Predictability and Time Homogeneity of Syntax in the Songs of Cassin’s Vireo (Vireo cassinii)

Many species of animals deliver vocalizations in sequences presumed to be governed by internal rules, though the nature and complexity of these syntactical rules have been investigated in relatively few species. Here I present an investigation into the song syntax of fourteen male Cassin’s Vireos (Vireo cassinii), a species whose song sequences are highly temporally structured. I compare their song sequences to three candidate models of varying levels of complexity–zero-order, first-order and second-order Markov models–and employ novel methods to interpolate between these three models. A variety of analyses, including sequence simulations, Fisher’s exact tests, and model likelihood analyses, showed that the songs of this species are too complex to be described by a zero-order or first-order Markov model. The model that best fit the data was intermediate in complexity between a first- and second-order model, though I also present evidence that some transition probabilities are conditioned on up to three preceding phrases. In addition, sequences were shown to be predictable with more than 54% accuracy overall, and predictability was positively correlated with the rate of song delivery. An assessment of the time homogeneity of syntax showed that transition probabilities between phrase types are largely stable over time, but that there was some evidence for modest changes in syntax within and between breeding seasons, a finding that I interpret to represent changes in breeding stage and social context rather than irreversible, secular shifts in syntax over time. These findings constitute a valuable addition to our understanding of bird song syntax in free-living birds, and will contribute to future attempts to understand the evolutionary importance of bird song syntax in avian communication.