Linking shifts in bacterial community with changes in dissolved organic matter pool in a tropical lake

Bacterioplankton communities have a pivotal role in the global carbon cycle. Still the interaction between microbial community and dissolved organic matter (DOM) in freshwater ecosystems remains poorly understood. Here, we report results from a 12-day mesocosm study performed in the epilimnion of a tropical lake, in which inorganic nutrients and allochthonous DOM were supplemented under full light and shading. Although the production of autochthonous DOM triggered by nutrient addition was the dominant driver of changes in bacterial community structure, temporal covariations between DOM optical proxies and bacterial community structure revealed a strong influence of community shifts on DOM fate. Community shifts were coupled to a successional stepwise alteration of the DOM pool, with different fractions being selectively consumed by specific taxa Typical freshwater clades as Limnohabitans and Sporichthyaceae were associated with consumption of low molecular weight carbon, whereas Gammaproteobacteria and Flavobacteria utilized higher molecular weight carbon, indicating differences in DOM preference among Glades. Importantly. Verrucomicrobiaceae were important in the turnover of freshly produced autochthonous DOM, ultimately affecting light availability and dissolved organic carbon concentrations. Our findings suggest that taxonomically defined bacterial assemblages play definite roles when influencing DOM fate, either by changing specific fractions of the DOM pool or by regulating light availability and DOC levels. (C) 2019 Elsevier B.V. All rights reserved.Peer reviewe

Estrogen receptor transcription and transactivation: Estrogen receptor knockout mice - what their phenotypes reveal about mechanisms of estrogen action

Natural, synthetic and environmental estrogens have numerous effects on the development and physiology of mammals. Estrogen is primarily known for its role in the development and functioning of the female reproductive system. However, roles for estrogen in male fertility, bone, the circulatory system and immune system have been established by clinical observations regarding sex differences in pathologies, as well as observations following menopause or castration. The primary mechanism of estrogen action is via binding and modulation of activity of the estrogen receptors (ERs), which are ligand-dependent nuclear transcription factors. ERs are found in highest levels in female tissues critical to reproduction, including the ovaries, uterus, cervix, mammary glands and pituitary gland. Since other affected tissues have extremely low levels of ER, indirect effects of estrogen, for example induction of pituitary hormones that affect the bone, have been proposed. The development of transgenic mouse models that lack either estrogen or ER have proven to be valuable tools in defining the mechanisms by which estrogen exerts its effects in various systems. The aim of this article is to review the mouse models with disrupted estrogen signaling and describe the associated phenotypes

Quantifier-free encoding of invariants for hybrid systems

Hybrid systems are a clean modeling framework for embedded systems, which feature integrated discrete and continuous dynamics. A well-known source of complexity comes from the time invariants, which represent an implicit quan- tication of a constraint over all time points of a continuous transition. Emerging techniques based on Satisability Modulo Theory (SMT) have been found promising for the verication and validation of hybrid systems because they combine discrete reasoning with solvers for rst-order theories. However, these techniques are ecient for quantier-free theories and the current approaches have so far either ignored time invariants or have been limited to hybrid systems with linear constraints. In this paper, we propose a new method that encodes a class of hybrid systems into transition systems with quantier-free formulas. The method does not rely on expensive quantier elimination procedures. Rather, it exploits the sequential nature of the transition system to split the continuous evolution enforcing the invariants on the discrete time points. This way, we can encode all hybrid systems whose invariants can be expressed in terms of polynomial constraints. This pushes the application of SMT-based techniques beyond the standard linear case

Time-aware Relational Abstractions for Hybrid Systems

Hybrid Systems model both discrete switches and continuous dynamics and are suitable to represent embedded systems where discrete controllers interact with a physical plant. Relational abstraction is a new approach for verifying hybrid systems. In relational abstraction, the continuous dynamics in each location of the hybrid system is abstracted by a binary relation that relates the current value of the continuous variables with all future values of the variables that are reachable after a time elapse (continuous) transition. The abstract system is an innite-state system, which can be veried using k-induction or abstract interpretation. Existing techniques for computing relational abstractions are time-agnostic: they do not construct any relationship between the state variables and the time elapsed during the continuous evolution. Time-agnostic abstractions can not verify timing properties. We present a technique to compute a time-aware relational abstraction for verifying (timing-related) safety properties of cyber-physical systems. We show the eectiveness of the new abstraction on several case studies on which the previous techniques fail

HYCOMP - an SMT-based model checker for hybrid systems

HyComp is a model checker for hybrid systems based on Satisfiability Modulo Theories (SMT). HyComp takes as input networks of hybrid automata specified using the HyDI symbolic language. HyComp relies on the encoding of the network into an infinite-state transition system, which can be analyzed using SMT-based verification techniques (e.g. BMC, K-induction, IC3). The tool features specialized encodings of the automata network and can discretize various kinds of dynamics. HyComp can verify invariant and LTL properties, and scenario specifications; it can also perform synthesis of parameters ensuring the satisfaction of a given (invariant) property. All these features are provided either through specialized algorithms, as in the case of scenario or LTL verification, or applying off-the-shelf algorithms based on SMT. We describe the tool in terms of functionalities, architecture, and implementation, and we present the results of an experimental evaluation