Dysregulation of Kv3.4 channels in dorsal root ganglia following spinal cord injury.

Spinal cord injury (SCI) patients develop chronic pain involving poorly understood central and peripheral mechanisms. Because dysregulation of the voltage-gated Kv3.4 channel has been implicated in the hyperexcitable state of dorsal root ganglion (DRG) neurons following direct injury of sensory nerves, we asked whether such a dysregulation also plays a role in SCI. Kv3.4 channels are expressed in DRG neurons, where they help regulate action potential (AP) repolarization in a manner that depends on the modulation of inactivation by protein kinase C (PKC)-dependent phosphorylation of the channel\u27s inactivation domain. Here, we report that, 2 weeks after cervical hemicontusion SCI, injured rats exhibit contralateral hypersensitivity to stimuli accompanied by accentuated repetitive spiking in putative DRG nociceptors. Also in these neurons at 1 week after laminectomy and SCI, Kv3.4 channel inactivation is impaired compared with naive nonsurgical controls. At 2-6 weeks after laminectomy, however, Kv3.4 channel inactivation returns to naive levels. Conversely, Kv3.4 currents at 2-6 weeks post-SCI are downregulated and remain slow-inactivating. Immunohistochemistry indicated that downregulation mainly resulted from decreased surface expression of the Kv3.4 channel, as whole-DRG-protein and single-cell mRNA transcript levels did not change. Furthermore, consistent with Kv3.4 channel dysregulation, PKC activation failed to shorten the AP duration of small-diameter DRG neurons. Finally, re-expressing synthetic Kv3.4 currents under dynamic clamp conditions dampened repetitive spiking in the neurons from SCI rats. These results suggest a novel peripheral mechanism of post-SCI pain sensitization implicating Kv3.4 channel dysregulation and potential Kv3.4-based therapeutic interventions

Impaired Notch Signaling Promotes \u3cem\u3eDe novo\u3c/em\u3e Squamous Cell Carcinoma Formation

Signaling through Notch receptors in the skin has been implicated in the differentiation, proliferation, and survival of keratinocytes, as well as in the pathogenesis of basal cell carcinoma (BCC). To determine the composite function of Notch receptor–mediated signaling in the skin and overcome potential redundancies between receptors, conditional transgenic mice were generated that express the pan-Notch inhibitor, dominant-negative Mastermind Like 1 (DNMAML1), to repress all canonical [CBF-1/Suppressor of hairless/LAG-1 (CSL)–dependent] Notch signaling exclusively in the epidermis. Here, we report that DNMAML1 mice display hyperplastic epidermis and spontaneously develop cutaneous squamous cell carcinoma (SCC) as well as dysplastic precursor lesions, actinic keratoses. Mice expressing epidermal DNMAML1 display enhanced accumulation of nuclear ß-catenin and cyclin D1 in suprabasilar keratinocytes and in lesional cells from SCCs, which was also observed in human cutaneous SCC. These results suggest a model wherein CSL-dependent Notch signaling confers protection against cutaneous SCC. The demonstration that inhibition of canonical Notch signaling in mice leads to spontaneous formation of SCC and recapitulates the disease in humans yields fundamental insights into the pathogenesis of SCC and provides a unique in vivo animal model to examine the pathobiology of cutaneous SCC and for evaluating novel therapies

allodb: An R package for biomass estimation at globally distributed extratropical forest plots

Allometric equations for calculation of tree above-ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built-in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types

The History and Prehistory of Natural-Language Semantics

Contemporary natural-language semantics began with the assumption that the meaning of a sentence could be modeled by a single truth condition, or by an entity with a truth-condition. But with the recent explosion of dynamic semantics and pragmatics and of work on non- truth-conditional dimensions of linguistic meaning, we are now in the midst of a shift away from a truth-condition-centric view and toward the idea that a sentence’s meaning must be spelled out in terms of its various roles in conversation. This communicative turn in semantics raises historical questions: Why was truth-conditional semantics dominant in the first place, and why were the phenomena now driving the communicative turn initially ignored or misunderstood by truth-conditional semanticists? I offer a historical answer to both questions. The history of natural-language semantics—springing from the work of Donald Davidson and Richard Montague—began with a methodological toolkit that Frege, Tarski, Carnap, and others had created to better understand artificial languages. For them, the study of linguistic meaning was subservient to other explanatory goals in logic, philosophy, and the foundations of mathematics, and this subservience was reflected in the fact that they idealized away from all aspects of meaning that get in the way of a one-to-one correspondence between sentences and truth-conditions. The truth-conditional beginnings of natural- language semantics are best explained by the fact that, upon turning their attention to the empirical study of natural language, Davidson and Montague adopted the methodological toolkit assembled by Frege, Tarski, and Carnap and, along with it, their idealization away from non-truth-conditional semantic phenomena. But this pivot in explana- tory priorities toward natural language itself rendered the adoption of the truth-conditional idealization inappropriate. Lifting the truth-conditional idealization has forced semanticists to upend the conception of linguistic meaning that was originally embodied in their methodology

Intravitreally injected anti-VEGF antibody reduces brown fat in neonatal mice

Anti-vascular endothelial growth factor (VEGF) agents are the mainstay treatment for various angiogenesis-related retinal diseases. Currently, bevacizumab, a recombinant humanized anti-VEGF antibody, is trailed in retinopathy of prematurity, a vasoproliferative retinal disorder in premature infants. However, the risks of systemic complications after intravitreal injection of anti-VEGF antibody in infants are not well understood. In this study, we show that intravitreally injected anti-VEGF antibody is transported into the systemic circulation into the periphery where it reduces brown fat in neonatal C57BL/6 mice. A considerable amount of anti-VEGF antibody was detected in serum after intravitreal injection. Furthermore, in interscapular brown adipose tissue, we found lipid droplet accumulation, decreased VEGF levels, loss of vascular network, and decreased expression of mitochondriarelated genes, Ppargc1a and Ucp1, all of which are characteristics of "whitening" of brown fat. With increasing age and body weight, brown fat restored its morphology and vascularity. Our results show that there is a transient, but significant impact of intravitreally administered anti-VEGF antibody on brown adipose tissue in neonatal mice. We suggest that more attention should be focused on the metabolic and developmental significance of brown adipose tissue in bevacizumab treated retinopathy of prematurity infants. Copyright

Astrocytes: biology and pathology

Astrocytes are specialized glial cells that outnumber neurons by over fivefold. They contiguously tile the entire central nervous system (CNS) and exert many essential complex functions in the healthy CNS. Astrocytes respond to all forms of CNS insults through a process referred to as reactive astrogliosis, which has become a pathological hallmark of CNS structural lesions. Substantial progress has been made recently in determining functions and mechanisms of reactive astrogliosis and in identifying roles of astrocytes in CNS disorders and pathologies. A vast molecular arsenal at the disposal of reactive astrocytes is being defined. Transgenic mouse models are dissecting specific aspects of reactive astrocytosis and glial scar formation in vivo. Astrocyte involvement in specific clinicopathological entities is being defined. It is now clear that reactive astrogliosis is not a simple all-or-none phenomenon but is a finely gradated continuum of changes that occur in context-dependent manners regulated by specific signaling events. These changes range from reversible alterations in gene expression and cell hypertrophy with preservation of cellular domains and tissue structure, to long-lasting scar formation with rearrangement of tissue structure. Increasing evidence points towards the potential of reactive astrogliosis to play either primary or contributing roles in CNS disorders via loss of normal astrocyte functions or gain of abnormal effects. This article reviews (1) astrocyte functions in healthy CNS, (2) mechanisms and functions of reactive astrogliosis and glial scar formation, and (3) ways in which reactive astrocytes may cause or contribute to specific CNS disorders and lesions

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio