SMOC-1 interacts with both BMP and glypican to regulate BMP signaling in C. elegans.

Secreted modular calcium-binding proteins (SMOCs) are conserved matricellular proteins found in organisms from Caenorhabditis elegans to humans. SMOC homologs characteristically contain 1 or 2 extracellular calcium-binding (EC) domain(s) and 1 or 2 thyroglobulin type-1 (TY) domain(s). SMOC proteins in Drosophila and Xenopus have been found to interact with cell surface heparan sulfate proteoglycans (HSPGs) to exert both positive and negative influences on the conserved bone morphogenetic protein (BMP) signaling pathway. In this study, we used a combination of biochemical, structural modeling, and molecular genetic approaches to dissect the functions of the sole SMOC protein in C. elegans. We showed that CeSMOC-1 binds to the heparin sulfate proteoglycan GPC3 homolog LON-2/glypican, as well as the mature domain of the BMP2/4 homolog DBL-1. Moreover, CeSMOC-1 can simultaneously bind LON-2/glypican and DBL-1/BMP. The interaction between CeSMOC-1 and LON-2/glypican is mediated specifically by the EC domain of CeSMOC-1, while the full interaction between CeSMOC-1 and DBL-1/BMP requires full-length CeSMOC-1. We provide both in vitro biochemical and in vivo functional evidence demonstrating that CeSMOC-1 functions both negatively in a LON-2/glypican-dependent manner and positively in a DBL-1/BMP-dependent manner to regulate BMP signaling. We further showed that in silico, Drosophila and vertebrate SMOC proteins can also bind to mature BMP dimers. Our work provides a mechanistic basis for how the evolutionarily conserved SMOC proteins regulate BMP signaling.

Dynamic use of agriculture incentives to promote conservation.

A common problem in resource management concerns the offer of incentives to individuals and organizations to encourage their participation in conservation practices. For underlying acceptance rates that are not known initially, a structured process of annually offering different incentives and recording responses can guide decisions about the number of incentives to offer through time. We examined a dynamic model that includes combinations of different incentives that are offered to farmers each year, with the objective of strengthening participation in agricultural conservation. We considered 3 approaches for identifying incentive acceptance rates that measure participation, including an arbitrary rate assignment independent of incentive data; iterative averaging based on annual offers and acceptances; and Bayesian updating of expected acceptance rates with beta distributed rates and a binomial data distribution. We performed a proof-of-concept simulation that evaluated different strategies that utilize the estimated rates to offer incentives through time. The strategies we evaluated included matching offers to prior year acceptance rate estimates, possibly weighted by their precision; offering only the incentive with the largest estimated acceptance rate each year; and equally allocating offers among the incentives. We evaluated scenarios for non-stationarity in the underlying acceptance rates and considered alternatives for using offer data to deal with non-stationarity. Results indicated that the trajectory of future offers is marginally affected by variance weighting, and there is a strong influence of non-stationarity. Truncating data with a negative rate change accentuates the decline in an offer trajectory, whereas truncation with a positive rate change dampens the trajectory increase. We found that the way one handles variation in estimating acceptance rates, in particular non-stationarity, can have a substantial effect on the management of incentives, especially in the short term. The results can be generalized to allow for multiple changes in underlying rates over a project time horizon. We highlight the strong similarities between our framing of the incentives problem and the more general context of sequential experimentation, with its opportunity to improve conservation through adaptive learning.

Phenotypic characterization of diamond (dind), a Drosophila gene required for multiple aspects of cell division.

Many genes are required for the assembly of the mitotic apparatus and for proper chromosome behavior during mitosis and meiosis. A fruitful approach to elucidate the mechanisms underlying cell division is the accurate phenotypic characterization of mutations in these genes. Here, we report the identification and characterization of diamond (dind), an essential Drosophila gene required both for mitosis of larval brain cells and for male meiosis. Larvae homozygous for any of the five EMS-induced mutations die in the third-instar stage and exhibit multiple mitotic defects. Mutant brain cells exhibit poorly condensed chromosomes and frequent chromosome breaks and rearrangements; they also show centriole fragmentation, disorganized mitotic spindles, defective chromosome segregation, endoreduplicated metaphases, and hyperploid and polyploid cells. Comparable phenotypes occur in mutant spermatogonia and spermatocytes. The dind gene encodes a non-conserved protein with no known functional motifs. Although the Dind protein exhibits a rather diffuse localization in both interphase and mitotic cells, fractionation experiments indicate that some Dind is tightly associated with the chromatin. Collectively, these results suggest that loss of Dind affects chromatin organization leading to defects in chromosome condensation and integrity, which in turn affect centriole stability and spindle assembly. However, our results do not exclude the possibility that Dind directly affects some behaviors of the spindle and centrosomes.

The potential for citizen science to produce reliable and useful information in ecology.

We examined features of citizen science that influence data quality, inferential power, and usefulness in ecology. As background context for our examination, we considered topics such as ecological sampling (probability based, purposive, opportunistic), linkage between sampling technique and statistical inference (design based, model based), and scientific paradigms (confirmatory, exploratory). We distinguished several types of citizen science investigations, from intensive research with rigorous protocols targeting clearly articulated questions to mass-participation internet-based projects with opportunistic data collection lacking sampling design, and examined overarching objectives, design, analysis, volunteer training, and performance. We identified key features that influence data quality: project objectives, design and analysis, and volunteer training and performance. Projects with good designs, trained volunteers, and professional oversight can meet statistical criteria to produce high-quality data with strong inferential power and therefore are well suited for ecological research objectives. Projects with opportunistic data collection, little or no sampling design, and minimal volunteer training are better suited for general objectives related to public education or data exploration because reliable statistical estimation can be difficult or impossible. In some cases, statistically robust analytical methods, external data, or both may increase the inferential power of certain opportunistically collected data. Ecological management, especially by government agencies, frequently requires data suitable for reliable inference. With standardized protocols, state-of-the-art analytical methods, and well-supervised programs, citizen science can make valuable contributions to conservation by increasing the scope of species monitoring efforts. Data quality can be improved by adhering to basic principles of data collection and analysis, designing studies to provide the data quality required, and including suitable statistical expertise, thereby strengthening the science aspect of citizen science and enhancing acceptance by the scientific community and decision makers.

Potencial de la Ciencia Ciudadana para Producir Información Útil y Confiable en la Ecología Resumen Examinamos las características de la ciencia ciudadana que influyen sobre la calidad de datos, el poder inferencial, y la utilidad en la ecología. Consideramos temas como el muestreo ecológico (basado en probabilidad, deliberado, oportunista), la conexión entre la técnica de muestreo y la inferencia estadística (basada en diseño, basada en modelo) y los paradigmas científicos (confirmatorio, exploratorio) como trasfondo contextual para nuestra evaluación. Distinguimos varios tipos de investigación de ciencia ciudadana, desde investigación intensiva con protocolos rigurosos enfocados en preguntas claramente articuladas hasta proyectos de participación masiva en plataformas de internet con recolección de datos oportunistas carentes de un diseño de muestreo, y examinamos los objetivos generales, el diseño, el análisis, y la preparación de los voluntarios y el desempeño. Identificamos características clave que influyen sobre la calidad de los datos: los objetivos del proyecto, el diseño y el análisis, y la preparación y el desempeño de los voluntarios. Los proyectos con buenos diseños, voluntarios preparados, y supervisión profesional pueden cumplir con criterios estadísticos para producir datos de alta calidad con un fuerte poder inferencial, y por lo tanto son muy adecuados para los objetivos de investigación ecológica. Los proyectos con una recolección oportunista de datos, un diseño de muestreo ínfimo o nulo, y una preparación mínima de los voluntarios son más adecuados para los objetivos generales relacionados con la educación pública o la exploración de datos ya que la estimación estadística confiable puede ser complicada o imposible. En algunos casos los métodos analíticos estadísticamente sólidos, los datos externos, o ambos, pueden incrementar el poder inferencial de ciertos datos recolectados de manera oportunista. El manejo ecológico, en especial el que realizan las agencias gubernamentales, requiere frecuentemente de datos apropiados para una inferencia confiable. Con protocolos estandarizados, métodos analíticos modernos, y programas supervisados correctamente, la ciencia ciudadana puede contribuir de forma valiosa a la conservación al incrementar el alcance de los esfuerzos de monitoreo para una especie. La calidad de datos puede mejorarse si se adhiere a los principios básicos de la recolección y análisis de datos, se diseñan los estudios para que proporcionen la calidad requerida de datos, y si se incluye una pericia estadística adecuada, fortaleciendo así el aspecto científico de la ciencia ciudadana y aumentando su aceptación dentro de la comunidad científica y con quienes toman las decisiones.

Cell cycle-dependent regulation of Greatwall kinase by protein phosphatase 1 and regulatory subunit 3B.

Greatwall (Gwl) kinase plays an essential role in the regulation of mitotic entry and progression. Mitotic activation of Gwl requires both cyclin-dependent kinase 1 (CDK1)-dependent phosphorylation and its autophosphorylation at an evolutionarily conserved serine residue near the carboxyl terminus (Ser-883 in Xenopus). In this study we show that Gwl associates with protein phosphatase 1 (PP1), particularly PP1γ, which mediates the dephosphorylation of Gwl Ser-883. Consistent with the mitotic activation of Gwl, its association with PP1 is disrupted in mitotic cells and egg extracts. During mitotic exit, PP1-dependent dephosphorylation of Gwl Ser-883 occurs prior to dephosphorylation of other mitotic substrates; replacing endogenous Gwl with a phosphomimetic S883E mutant blocks mitotic exit. Moreover, we identified PP1 regulatory subunit 3B (PPP1R3B) as a targeting subunit that can direct PP1 activity toward Gwl. PPP1R3B bridges PP1 and Gwl association and promotes Gwl Ser-883 dephosphorylation. Consistent with the cell cycle-dependent association of Gwl and PP1, Gwl and PPP1R3B dissociate in M phase. Interestingly, up-regulation of PPP1R3B facilitates mitotic exit and blocks mitotic entry. Thus, our study suggests PPP1R3B as a new cell cycle regulator that functions by governing Gwl dephosphorylation.

Double-Loop Learning in Adaptive Management: The Need, the Challenge, and the Opportunity.

Adaptive management addresses uncertainty about the processes influencing resource dynamics, as well as the elements of decision making itself. The use of management to reduce both kinds of uncertainty is known as double-loop learning. Though much work has been done on the theory and procedures to address structural uncertainty, there has been less progress in developing an explicit approach for institutional learning about decision elements. Our objective is to describe evidence-based learning about the decision elements, as a complement to the formal "learning by doing" framework for reducing structural uncertainties. Adaptive management is described as a multi-phase approach to management and learning, with a set-up phase of identifying stakeholders, objectives, and other decision elements; an iterative phase that uses these elements in an ongoing cycle of technical learning about system structure and management impacts; and an institutional learning phase involving the periodic reconsideration of the decision elements. We describe a framework for institutional learning that is complementary to that of technical learning, including uncertainty metrics, propagation of change, and mechanisms and consequences of change over time. Operational issues include ways to recognize when the decision elements should be revisited, which elements should be adjusted, and how alternatives can be identified and incorporated based on experience and management performance. We discuss the application of this framework in decision making for renewable natural resources. As important as it is to learn about the processes driving resource dynamics, learning about the elements of the decision architecture is equally, if not more, important.

RZZ and Mad1 dynamics in Drosophila mitosis.

The presence or absence of Mad1 at kinetochores is a major determinant of spindle assembly checkpoint (SAC) activity, the surveillance mechanism that delays anaphase onset if one or more kinetochores remain unattached to spindle fibers. Among the factors regulating the levels of Mad1 at kinetochores is the Rod, Zw10, and Zwilch (RZZ) complex, which is required for Mad1 recruitment through a mechanism that remains unknown. The relative dynamics and interactions of Mad1 and RZZ at kinetochores have not been extensively investigated, although Mad1 has been reported to be stably recruited to unattached kinetochores. In this study, we directly compare Mad1-green fluorescent protein (GFP) turnover dynamics on unattached Drosophila kinetochores with that of RZZ, tagged either with GFP-Rod or GFP-Zw10. We find that nearly 40 % of kinetochore-bound Mad1 has a significant dynamic component, turning over with a half-life of 12 s. RZZ in contrast is essentially stable on unattached kinetochores. In addition, we report that a fraction of RZZ and Mad1 can co-immunoprecipitate, indicating that the genetically determined recruitment hierarchy (in which Mad1 depends on RZZ) may reflect a physical association of the two complexes.

Resilience and Resource Management.

Resilience is an umbrella concept with many different shades of meaning. The use of the term has grown over the past several decades to the point that by now, many disciplines have their own definitions and metrics. In this paper, we aim to provide a context and focus for linkages of resilience to natural resources management. We consider differences and similarities in resilience as presented in several disciplines relevant to resource management. We present a conceptual framework that includes environmental drivers, management interventions, and system responses cast in terms of system resilience, as well as a process for decision making that allows learning about system resilience through experience and incorporation of that learning into management. We discuss the current state of operational management for resilience, and suggest ways to improve it. Finally, we describe the challenges in managing for resilience and offer some recommendations about the scientific information needs and scientific issues relevant to making resilience a more meaningful component of natural resources management.

Tandem deprotection-dimerization-macrocyclization route to C(2) symmetric cyclo-tetrapeptides.

Dimerization-macrocyclization has been a long-standing problem in the cyclization of peptides since, together with the desired cyclic product, many cyclic oligomers and linear polymers may also be formed during the reaction. Therefore, the development of a process that affords the cyclic dimer predominantly is difficult. A novel and versatile strategy for the synthesis of symmetric cyclo-tetrapeptides by palladium-promoted tandem deprotection/cyclo-dimerization from readily available Cbz-dipeptidoyl benzotriazolides is reported (Cbz=carboxybenzyl).

Adaptive management: from more talk to real action.

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.

Generation of a highly specific and potent antibody against Ce-lamin/LMN-1.

High quality antibodies are useful tools for research in cell and developmental biology. We have obtained highly specific and potent guinea pig-derived polyclonal antibodies against Ce-lamin/ LMN-1 . Western blotting experiments using these antibodies demonstrated that maternally loaded Ce-lamin/ LMN-1 protein is very stable, can perdure through embryonic and larval development and remain detectable in homozygous null lmn-1 mutant adults.

A systematic review of present and future pharmaco-structural therapies for hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a common contemporary, treatable, genetic disorder that can be compatible with normal longevity. While current medical therapies are ubiquitous, they are limited by a lack of solid evidence, are often inadequate, poorly tolerated, and do not alter the natural disease course. As such, there has long been a need for effective, evidence-based, and targeted disease-modifying therapies for HCM. In this review, we redefine HCM as a treatable condition, evaluate current strategies for therapeutic intervention, and discuss novel myosin inhibitors. The majority of patients with HCM have elevated left ventricular outflow tract gradients, which predicts worse symptoms and adverse outcomes. Conventional pharmacological therapies for symptomatic HCM can help improve symptoms but are often inadequate and poorly tolerated. Septal reduction therapies (surgical myectomy and alcohol septal ablation) can safely and effectively reduce refractory symptoms and improve outcomes in patients with obstructive HCM. However, they require expertise that is not universally available and are not without risks. Currently, available therapies do not alter the disease course or the progressive cardiac remodeling that ensues, nor subsequent heart failure and arrhythmias. This has been regarded as an unmet need in the care of HCM patients. Novel targeted pharmacotherapies, namely cardiac myosin inhibitors, have emerged to reverse key pathophysiological changes and alter disease course. Their favorable outcomes led to the early Food and Drug Administration approval of mavacamten, a first-in-class myosin modulator, changing the paradigm for the pharmacological treatment of HCM.

Conformationally assisted lactamizations for the synthesis of symmetrical and unsymmetrical bis-2,5-diketopiperazines.

Open-chain N-Cbz-protected-peptidoyl benzotriazolides are converted by a novel lactamization strategy using proline as a turn introducer into both symmetrical (5a-c and 11a-c) and unsymmetrical (19a-e) bis-2,5-diketopiperazines (bis-2,5-DKPs), previously recognized as difficult targets.

Four conservation challenges and a synthesis.

Conservation and management of biological systems involves decision-making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue-specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences.

C. elegans SMOC-1 interacts with both BMP and glypican to regulate BMP signaling.

Secreted modular calcium binding (SMOC) proteins are conserved matricellular proteins found in organisms from C. elegans to humans. SMOC homologs characteristically contain one or two extracellular calcium (EC) binding domain(s) and one or two thyroglobulin type-1 (TY) domain(s). SMOC proteins in Drosophila and Xenopus have been found to interact with cell surface heparan sulfate protein glycans (HSPGs) to exert both positive and negative influences on the conserved bone morphogenetic protein (BMP) signaling pathway. In this study, we used a combination of biochemical, structural modeling, and molecular genetic approaches to dissect the functions of the sole SMOC protein in C. elegans . We showed that SMOC-1 binds LON-2/glypican, as well as the mature domain of DBL-1/BMP. Moreover, SMOC-1 can simultaneously bind LON-2/glypican and DBL-1/BMP. The interaction between SMOC-1 and LON-2/glypican is mediated by the EC domain of SMOC-1, while the interaction between SMOC-1 and DBL-1/BMP involves full-length SMOC-1. We further showed that while SMOC-1(EC) is sufficient to promote BMP signaling when overexpressed, both the EC and TY domains are required for SMOC-1 function at the endogenous locus. Finally, when overexpressed, SMOC-1 can promote BMP signaling in the absence of LON-2/glypican. Taken together, our findings led to a model where SMOC-1 functions both negatively in a LON-2-dependent manner and positively in a LON-2-independent manner to regulate BMP signaling. Our work provides a mechanistic basis for how the evolutionarily conserved SMOC proteins regulate BMP signaling.

A convenient synthesis of difficult medium-sized cyclic peptides by Staudinger mediated ring-closure.

Novel, efficient and mild preparation of 7- and 8-membered cyclic di- and 10-membered cyclic tripeptides containing α-, ß- or γ-amino acid residues is effected by a Staudinger-mediated ring closure. Medium-sized cyclic di- and tripeptides--recognized as difficult targets--were obtained in moderate to good yields according to a straightforward sequence. Empirical force-field calculations were undertaken to determine their conformational behaviors and showed high levels of similarity with X-ray results. A computational study at the B3LYP/6-31+G** level of theory afforded information regarding the impact of the sequence, ring-size and substitution on the activation barriers for the cyclization of azido peptide thioesters.

Partial observability and management of ecological systems.

The actual state of ecological systems is rarely known with certainty, but management actions must often be taken regardless of imperfect measurement (partial observability). Because of the difficulties in accounting for partial observability, it is usually treated in an ad hoc fashion, or simply ignored altogether. Yet incorporating partial observability into decision processes lends a realism that has the potential to improve ecological outcomes significantly. We review frameworks for dealing with partial observability, focusing specifically on dynamic ecological systems with Markovian transitions, i.e., transitions among system states that are influenced by the current system state and management action over time. Fully observable states are represented in an observable Markov decision process (MDP), whereas obscure or hidden states are represented in a partially observable process (POMDP). POMDPs can be seen as a natural extension of observable MDPs. Management under partial observability generalizes the situation for complete observability, by recognizing uncertainty about the system's state and incorporating sequential observations associated with, but not the same as, the states themselves. Decisions that otherwise would depend on the actual state must be based instead on state probability distributions ("belief states"). Partial observability requires adaptation of the entire decision process, including the use of belief states and Bayesian updates, valuation that includes expectations over observations, and optimal strategy that identifies actions for belief states over a continuous belief space. We compare MDPs and POMDPs and highlight POMDP applications to some common ecological problems. We clarify the structure and operations, approaches for finding solutions, and analytic challenges of POMDPs for practicing ecologists. Both observable and partially observable MDPs can use an inductive approach to identify optimal strategies and values, with a considerable increase in mathematical complexity with POMDPs. Better understanding of POMDPs can help decision makers manage imperfectly measured ecological systems more effectively.

Compartmentalization of telomeres through DNA-scaffolded phase separation.

Telomeres form unique nuclear compartments that prevent degradation and fusion of chromosome ends by recruiting shelterin proteins and regulating access of DNA damage repair factors. To understand how these dynamic components protect chromosome ends, we combine in vivo biophysical interrogation and in vitro reconstitution of human shelterin. We show that shelterin components form multicomponent liquid condensates with selective biomolecular partitioning on telomeric DNA. Tethering and anomalous diffusion prevent multiple telomeres from coalescing into a single condensate in mammalian cells. However, telomeres coalesce when brought into contact via an optogenetic approach. TRF1 and TRF2 subunits of shelterin drive phase separation, and their N-terminal domains specify interactions with telomeric DNA in vitro. Telomeric condensates selectively recruit telomere-associated factors and regulate access of DNA damage repair factors. We propose that shelterin mediates phase separation of telomeric chromatin, which underlies the dynamic yet persistent nature of the end-protection mechanism.

Adaptive management of natural resources--framework and issues.

Adaptive management, an approach for simultaneously managing and learning about natural resources, has been around for several decades. Interest in adaptive decision making has grown steadily over that time, and by now many in natural resources conservation claim that adaptive management is the approach they use in meeting their resource management responsibilities. Yet there remains considerable ambiguity about what adaptive management actually is, and how it is to be implemented by practitioners. The objective of this paper is to present a framework and conditions for adaptive decision making, and discuss some important challenges in its application. Adaptive management is described as a two-phase process of deliberative and iterative phases, which are implemented sequentially over the timeframe of an application. Key elements, processes, and issues in adaptive decision making are highlighted in terms of this framework. Special emphasis is given to the question of geographic scale, the difficulties presented by non-stationarity, and organizational challenges in implementing adaptive management.

Passive and active adaptive management: approaches and an example.

Adaptive management is a framework for resource conservation that promotes iterative learning-based decision making. Yet there remains considerable confusion about what adaptive management entails, and how to actually make resource decisions adaptively. A key but somewhat ambiguous distinction in adaptive management is between active and passive forms of adaptive decision making. The objective of this paper is to illustrate some approaches to active and passive adaptive management with a simple example involving the drawdown of water impoundments on a wildlife refuge. The approaches are illustrated for the drawdown example, and contrasted in terms of objectives, costs, and potential learning rates. Some key challenges to the actual practice of AM are discussed, and tradeoffs between implementation costs and long-term benefits are highlighted.