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Abstract Experimental studies have demonstrated that solid solutions of minerals from the alunite group, with chemical compositions intermediate between the Al and Fe end-members, can be readily synthesized in the laboratory. In contrast, up until about a dozen years ago, there were no confirmed reports of alunite group minerals with intermediate Al-Fe compositions in natural settings, leading some to suggest that minerals with such compositions might not exist in nature. In recent years, however, alunite group minerals with intermediate Al-Fe compositions have been documented in a few isolated locations, which were previously limited to basalt-hosted acid-sulfate fumarole deposits and acid mine drainage pit lakes. These occurrences contrast with nearly all other reports of minerals from this group, whose measured chemical compositions are very close to either the Al or Fe end-members. Here, we report jarosite-alunite solid solutions containing approximately equal amounts of Al and Fe, which are found in mineralized fractures of the Aztec Sandstone in southeast Nevada. Analysis of the minerals by X-ray diffraction, Raman spectroscopy, and visible-near infrared spectroscopy confirms that they are bona fide solid solutions and not intimate mixtures of end-member minerals. This study represents the first documented occurrence of alunite group solid solutions with intermediate Al-Fe compositions in sedimentary rocks. The results further demonstrate that alunite group minerals with a wide range of Al-Fe compositions occur naturally and can persist for millions of years or more in natural systems. 

An analysis of the language we use in scientific practice is critical to developing more rigorous and sound methodologies. This article argues that how certain methods of description are commonly employed in cognitive science risks obscuring important features of an agent’s cognition. We propose to make explicit a method of description whereby the concept of cognitive distinctions is the core principle. A model of referential communication is developed and analyzed as a platform to compare methods of description. We demonstrate that cognitive distinctions, realized in a graph theoretic formalism, better describe the behavior and perspective of a simple model agent than other, less systematic or natural language–dependent methods. We then consider how different descriptions relate to one another in the broader methodological framework of minimally cognitive behavior. Finally, we explore the consequences of, and challenges for, cognitive distinctions as a useful concept and method in the tool kit of cognitive scientists. 

Synapses of retinal rod photoreceptors involve deep invaginations occupied by second-order rod bipolar cell (RBP) and horizontal cell (HC) dendrites. Synaptic vesicles are released into this invagination at multiple sites beneath an elongated presynaptic ribbon. To study the impact of this architecture on glutamate diffusion and receptor activity, we reconstructed four rod terminals and their postsynaptic dendrites from serial electron micrographs of the mouse retina. We incorporated these structures into anatomically realistic Monte Carlo simulations of neurotransmitter diffusion and receptor activation. By comparing passive diffusion of glutamate in realistic structures with geometrically simplified models, we found that glutamate exits anatomically realistic synapses 10-fold more slowly than previously predicted. Constraining simulations with physiological data, we modeled activity of EAAT5 glutamate transporters in rods, AMPA receptors on HC dendrites, and metabotropic glutamate receptors (mGluR6) on RBP dendrites. Simulations suggested that ∼3,000 EAAT5 populate rod membranes. While uptake by surrounding glial Müller cells retrieves most glutamate released by rods, binding and uptake by EAAT5 influence RBP kinetics. Glutamate persistence allows mGluR6 on RBP dendrites to integrate the stream of vesicles released by rods in darkness. Glutamate’s tortuous diffusional path confers quantal variability, as release from nearby ribbon sites exerts larger effects on RBP and HC receptors than release from more distant sites. Temporal integration supports slower sustained release rates, but additional quantal variability can impede postsynaptic detection of changes in release produced by rod light responses. These results show an example of the profound impact that synaptic architecture can have on postsynaptic responses. 

Abstract In this work, we present a new approach to produce spectroscopic constants and model first-principles synthetic spectra for all molecules of astrophysical interest. We have generalized our previous diatomic molecule simulation framework, employing transition-optimized shifted Hermite (TOSH) theory, thereby enabling the modeling of polyatomic rotational constants for molecules with three or more atoms. These capabilities are now provided by our new code Epimetheus. As a first validation of our approach, we confront our predictions and assess their accuracy against the well-studied triatomic molecule ozone 666 (¹⁶O₃), in addition to eight of its potential isotopomers: ozone 668 (¹⁶O¹⁶O¹⁸O), 686 (¹⁶O¹⁸O¹⁶O), 667 (¹⁶O¹⁶O¹⁷O), 676 (¹⁶O¹⁷O¹⁶O), 688 (¹⁶O¹⁸O¹⁸O), 868 (¹⁸O¹⁶O¹⁸O), 888 (¹⁸O₃), and 777 (¹⁷O₃). We then assess the accuracy of these rotational constants using the Epimetheus data in our code Pandora, and generate synthetic molecular spectra. The ozone spectra presented here are purely infrared and not Raman. Epimetheus builds upon the work from our previous code Prometheus, which used the TOSH theory to account for anharmonicity for the fundamentalν = 0 → ν = 1 band, going further to now account for triatomic molecules. This is combined with thermal profile modeling for the rotational transitions. We have found that this extended method performs well, typically approximating the spectroscopic constants with errors of less than 2%. Some issues do arise depending on the symmetry group of the ozone isotopomer. From these spectroscopic constants and using our own spectral modeling code, we show that we can provide the data to produce appreciable molecular spectra, which are good approximations until high-resolution studies can be done. 

Long-term potentiation (LTP) is a biochemical process that underlies learning in excitatory glutamatergic synapses in the Central Nervous System (CNS). A critical early driver of LTP is autophosphorylation of the abundant postsynaptic enzyme, Ca²⁺/calmodulin-dependent protein kinase II (CaMKII). Autophosphorylation is initiated by Ca²⁺flowing through NMDA receptors activated by strong synaptic activity. Its lifetime is ultimately determined by the balance of the rates of autophosphorylation and of dephosphorylation by protein phosphatase 1 (PP1). Here we have modeled the autophosphorylation and dephosphorylation of CaMKII during synaptic activity in a spine synapse using MCell4, an open source computer program for creating particle-based stochastic, and spatially realistic models of cellular microchemistry. The model integrates four earlier detailed models of separate aspects of regulation of spine Ca²⁺and CaMKII activity, each of which incorporate experimentally measured biochemical parameters and have been validated against experimental data. We validate the composite model by showing that it accurately predicts previous experimental measurements of effects of NMDA receptor activation, including high sensitivity of induction of LTP to phosphatase activityin vivo,and persistence of autophosphorylation for a period of minutes after the end of synaptic stimulation. We then use the model to probe aspects of the mechanism of regulation of autophosphorylation of CaMKII that are difficult to measurein vivo. We examine the effects of “CaM-trapping,” a process in which the affinity for Ca²⁺/CaM increases several hundred-fold after autophosphorylation. We find that CaM-trapping does not increase the proportion of autophosphorylated subunits in holoenzymes after a complex stimulus, as previously hypothesized. Instead, CaM-trapping may dramatically prolong the lifetime of autophosphorylated CaMKII through steric hindrance of dephosphorylation by protein phosphatase 1. The results provide motivation for experimental measurement of the extent of suppression of dephosphorylation of CaMKII by bound Ca²⁺/CaM. The composite MCell4 model of biochemical effects of complex stimuli in synaptic spines is a powerful new tool for realistic, detailed dissection of mechanisms of synaptic plasticity.