The guanine nucleotide exchange factor Vav2 is a negative regulator of parathyroid hormone receptor/G(q) signaling.

The parathyroid hormone receptor (PTHR) is a class B G protein-coupled receptor (GPCR) that mediates the endocrine and paracrine effects of parathyroid hormone and related peptides through the activation of phospholipase C beta-, adenylyl cyclase-, mitogen-activated protein kinase-, and beta-arrestin-initiated signaling pathways. It is currently not clear how specificity among these downstream signaling pathways is achieved. A possible mechanism involves adaptor proteins that affect receptor/effector coupling. In a proteomic screen with the PTHR C terminus, we identified vav2, a guanine nucleotide exchange factor (GEF) for Rho GTPases, as a PTHR-interacting protein. The core domains of vav2 bound to the intracellular domains of the PTHR independent of receptor activation. In addition, vav2 specifically interacted with activated G alpha(q) but not with G alpha(s) subunits, and it competed with PTHR for coupling to G alpha(q). Consistent with its specific interaction with G alpha(q), vav2 impaired G(q)-mediated inositol phosphate generation but not G(s)-mediated cAMP generation. This inhibition of G(q) signaling was specific for PTHR signaling, compared with other G(q)-coupled GPCRs. Moreover, the benefit for PTHR-mediated inositol phosphate generation in the absence of vav2 required the ezrin binding domain of Na+/H+-exchanger regulatory factor 1. Our results show that a RhoA GEF can specifically interact with a GPCR and modulate its G protein signaling specificity

Script Combination for Enhanced Story Understanding and Story Generation Systems

Scripts, knowledge structures defining sequences of events in stereotypical social situations, were traditionally used to simulate the ways in which people can infer unstated details in understanding a story. In this paper, we describe the MUltiple SCRipt AcTivator (MUSCRAT), and the Script Combination Applier Mechanism (SCAM), significant enhancements of Cullingford’s Script Applier Mechanism which accomplish two novel aims. One system, MUSCRAT, is able to activate more than one script and use them during a story understanding process. The second system, SCAM, uses scripts for story generation, using script variables as “terminals” for combining two or more scripts together to create complex narrative situation structures. The combinational abilities of these systems are enhanced by the fact that the scripts are represented not using linguistic elements but using decompositions into abstract conceptual primitives. We also discuss how some of the perceived weaknesses of scripts stemming from prior work may be overcome in systems that represent general thinking and reasoning processes as combined instantiations of standardized and generalized memory episodes

Profile shape dependence in backscattered ultraviolet satellite retrievals of total ozone

Total ozone operational algorithms use climatological mean ozone profiles. When the actual ozone profiles have significantly different shapes versus the climatology and the solar zenith angles are large, retrieved total ozone will have an error. Recalibrated SBUV profiles are used to estimate this error. Preliminary results suggest that, on the average, the change and variation in significant profiles shapes can to a large degree be estimated by the SBUV derived profiles. Preliminary results suggest the average error in the report algorithm ozone trend (trend in reported ozone) from profile shape is relatively small during the north hemisphere winter (less than 2 percent) for solar zenith angles less than 82 degrees (for 60 degrees North Latitude)

Proteolytic cleavage of the extracellular domain affects signaling of parathyroid hormone 1 receptor

Parathyroid hormone 1 receptor (PTH1R) is a member of the class B family of G protein-coupled receptors, which are characterized by a large extracellular domain required for ligand binding. We have previously shown that the extracellular domain of PTH1R is subject to metalloproteinase cleavage in vivo that is regulated by ligand-induced receptor trafficking and leads to impaired stability of PTH1R. In this work, we localize the cleavage site in the first loop of the extracellular domain using amino-terminal protein sequencing of purified receptor and by mutagenesis studies. We further show, that a receptor mutant not susceptible to proteolytic cleavage exhibits reduced signaling to G(s) and increased activation of G(q) compared to wild-type PTH1R. These findings indicate that the extracellular domain modulates PTH1R signaling specificity, and that its cleavage affects receptor signaling

Draft Genome Sequence of Frankia Strain G2, a Nitrogen-Fixing Actinobacterium Isolated from Casuarina equisetifolia and Able To Nodulate Actinorhizal Plants of the Order Rhamnales

Frankia sp. strain G2 was originally isolated from Casuarina equisetifolia and is characterized by its ability to nodulate actinorhizal plants of the Rhamnales order, but not its original host. It represents one of the largest Frankia genomes so far sequenced (9.5 Mbp)

Promises and pitfalls of digital knowledge exchange resulting from the COVID-19 pandemic

In this article, we integrate our authorship experiences with insights from nine interviews of knowledge exchange practitioners at the Canadian Forest Service about challenges and opportunities of digital knowledge exchange (KE) brought on by the COVID-19 pandemic. We aim to inform how best to maintain effective KE practices and processes in a digital-first world. Interpersonal trust and relationships are pivotal to effective knowledge exchange; thus, removing these dimensions risks losing aspects of social learning, informal and meaningful discussions, and personal connections that affect how we interpret and respond to subtle affective and social cues. For KE practitioners, lack of in-person interactions risks internal KE coordination and relevance of KE work, and diminished ability to predict and respond to user needs. However, the accelerated digital adoption has increased reach and accessibility for diverse people to exchange knowledge, and enables more frequent and rapid response to issues and events by virtually gathering diverse people almost instantly. The acceleration in digital innovation and culture has thus resulted in new tools and diversified approaches for the KE toolbox to inform decisions and practices. The long-term sustainability and effectiveness of digital KE depend on two interconnected factors: addressing the persistence of the digital divide and people’s abilities to make and maintain meaningful social connections in the absence of regular face-to-face contact. We thus offer three considerations to guide KE efforts and initiative in a digital-first world: (1) consider both digital divide and equity; (2) revisit user needs and preferences for KE to address the diversity of users, and (3) leverage the diversification of KE approaches and innovations

Interleaving a Symbolic Story Generator with a Neural Network-Based Large Language Model

Research in deep learning has recently produced models of natural language that are capable of generating natural language output which, at a glance, has strong similarities to that written by intelligent humans. However, the texts produced by deep learning-based large language models (LLMs), upon deeper examination, reveal the challenges that they have in producing outputs that maintain logical coherence. One specific application area of interest for LLMs is in fictional narrative generation, a mode of operation in which stories are generated by the model in response to a prompt text that indicates the start of a story or the desired style of writing to be produced. In this paper we present an initial study into a method for combining an LLM with a symbolic system to perform story generation. The method generates stories by repeatedly prompting the LLM by interleaving the output of a state-of-the-art LLM with the output of a classic story generation system, while attempting to control and shape the output of the LLM. We present a number of stories generated with a prototype interleaving system, and discuss the qualities of the stories and challenges for future development of the method