Get Your Own Street Cred: An Argument for Trademark Protection for Street Art

Street art is visual art created in public spaces, many times at the behest of the communities in which the work is created. It is a derivative of graffiti, which is the illicit marking of public locations, usually on buildings or train cars. Retailers’ appropriation of street art and graffiti is becoming commonplace, causing confusion in the market. As a result, street artists have filed an increasing number of copyright and trademark infringement lawsuits to protect their intellectual property rights. There is a debate regarding whether these artists are entitled to trademark protection given the expressive nature of their marks. Courts are reluctant to grant trademark protection since expressive works are traditionally protected under copyright law. Most street artists, as opposed to creators of “fine art,” however, use marks in a trademark manner to build reputations and identify the source of their works. This Note argues that courts should broadly interpret the Lanham Act’s “use in commerce” requirement to validate marks used by street artists. Street art substantially affects commerce and therefore should be covered by the Commerce Clause. Abroad interpretation furthers Congress’s intent under trademark law to prevent consumer confusion. In the alternative, this Note contemplates treatment of street artists under the eleemosynary standard reiterated by the Eleventh Circuit Court of Appeals in 2001 in Planetary Motion Inc. v. Techsplosion, Inc., and considers the possibility of adding a famous mark exception to the use in commerce requirement

A Graph Theoretic Approach for Generating Hypotheses About Phonetic Cues in Speech

Current models of speech perception suggest that combining acoustic cues and factoring out contextual variability allows listeners to recognize speech across different talkers. However, it remains unclear which specific cues are necessary and how their use varies between individual talkers. We use graph theoretic techniques to address these problems by constructing networks connecting talkers and possible cues. We identify subgraphs (Steiner trees) that connect talkers via cues consistently used to indicate specific phonemes. Classifiers trained on these cues match listeners\u27 data better than those trained on all cues, suggesting that Steiner trees can identify the cues necessary for speech recognition

LexFindR: A fast, simple, and extensible R package for finding similar words in a lexicon

Published 30 September 2021Language scientists often need to generate lists of related words, such as potential competitors. Theymay do this for purposes of experimental control (e.g., selecting items matched on lexical neighborhood but varying in word frequency), or to test theoretical predictions (e.g., hypothesizing that a novel type of competitor may impact word recognition). Several online tools are available, but most are constrained to a fixed lexicon and fixed sets of competitor definitions, and may not give the user full access to or control of source data. We present LexFindR, an open-source R package that can be easily modified to include additional, novel competitor types. LexFindR is easy to use. Because it can leverage multiple CPU cores and uses vectorized code when possible, it is also extremely fast. In this article, we present an overview of LexFindR usage, illustrated with examples.We also explain the details of how we implemented several standard lexical competitor types used in spoken word recognition research (e.g., cohorts, neighbors, embeddings, rhymes), and show how “lexical dimensions” (e.g., word frequency, word length, uniqueness point) can be integrated into LexFindR workflows (for example, to calculate “frequency-weighted competitor probabilities”), for both spoken and visual word recognition research.This work was supported in part by U.S. National Science Foundation grants PAC 1754284 (JM, PI) and IGE NRT 1747486 (JM, PI). The authors are solely responsible for the content of this article. This work was also supported in part by the Basque Government through the BERC 2018-2021 program, and by the Agencia Estatal de Investigaci´on through BCBL Severo Ochoa excellence accreditation SEV-2015-0490

Macrophage TNF-α mediates parathion-induced airway hyperreactivity in guinea pigs.

Organophosphorus pesticides (OPs) are implicated in human asthma. We previously demonstrated that, at concentrations that do not inhibit acetylcholinesterase activity, the OP parathion causes airway hyperreactivity in guinea pigs as a result of functional loss of inhibitory M2 muscarinic receptors on parasympathetic nerves. Because macrophages are associated with asthma, we investigated whether macrophages mediate parathion-induced M2 receptor dysfunction and airway hyperreactivity. Airway physiology was measured in guinea pigs 24 h after a subcutaneous injection of parathion. Pretreatment with liposome-encapsulated clodronate induced alveolar macrophage apoptosis and prevented parathion-induced airway hyperreactivity in response to electrical stimulation of the vagus nerves. As determined by qPCR, TNF-α and IL-1β mRNA levels were increased in alveolar macrophages isolated from parathion-treated guinea pigs. Parathion treatment of alveolar macrophages ex vivo did not significantly increase IL-1β and TNF-α mRNA but did significantly increase TNF-α protein release. Consistent with these data, pretreatment with the TNF-α inhibitor etanercept but not the IL-1β receptor inhibitor anakinra prevented parathion-induced airway hyperreactivity and protected M2 receptor function. These data suggest a novel mechanism of OP-induced airway hyperreactivity in which low-level parathion activates macrophages to release TNF-α-causing M2 receptor dysfunction and airway hyperreactivity. These observations have important implications regarding therapeutic approaches for treating respiratory disease associated with OP exposures

GeneTIER: prioritization of candidate disease genes using tissue-specific gene expression profiles.

Motivation In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually. Results Here we present GeneTIER (Gene TIssue Expression Ranker), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias towards the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples. Availability and Implementation Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/ Contact: [email protected]

Robust Lexically Mediated Compensation for Coarticulation: Christmash Time Is Here Again

First published: 20 April 2021A long-standing question in cognitive science is how high-level knowledge is integrated with sensory input. For example, listeners can leverage lexical knowledge to interpret an ambiguous speech sound, but do such effects reflect direct top-down influences on perception or merely postperceptual biases? A critical test case in the domain of spoken word recognition is lexically mediated compensation for coarticulation (LCfC). Previous LCfC studies have shown that a lexically restored context phoneme (e.g., /s/ in Christma#) can alter the perceived place of articulation of a subsequent target phoneme (e.g., the initial phoneme of a stimulus from a tapes-capes continuum), consistent with the influence of an unambiguous context phoneme in the same position. Because this phoneme-to-phoneme compensation for coarticulation is considered sublexical, scientists agree that evidence for LCfC would constitute strong support for top–down interaction. However, results from previous LCfC studies have been inconsistent, and positive effects have often been small. Here, we conducted extensive piloting of stimuli prior to testing for LCfC. Specifically, we ensured that context items elicited robust phoneme restoration (e.g., that the final phoneme of Christma# was reliably identified as /s/) and that unambiguous context-final segments (e.g., a clear /s/ at the end of Christmas) drove reliable compensation for coarticulation for a subsequent target phoneme.We observed robust LCfC in a well-powered, preregistered experiment with these pretested items (N = 40) as well as in a direct replication study (N = 40). These results provide strong evidence in favor of computational models of spoken word recognition that include top–down feedback

A Chromosome 7 Pericentric Inversion Defined at Single-Nucleotide Resolution Using Diagnostic Whole Genome Sequencing in a Patient with Hand-Foot-Genital Syndrome.

Next generation sequencing methodologies are facilitating the rapid characterisation of novel structural variants at nucleotide resolution. These approaches are particularly applicable to variants initially identified using alternative molecular methods. We report a child born with bilateral postaxial syndactyly of the feet and bilateral fifth finger clinodactyly. This was presumed to be an autosomal recessive syndrome, due to the family history of consanguinity. Karyotype analysis revealed a homozygous pericentric inversion of chromosome 7 (46,XX,inv(7)(p15q21)x2) which was confirmed to be heterozygous in both unaffected parents. Since the resolution of the karyotype was insufficient to identify any putatively causative gene, we undertook medium-coverage whole genome sequencing using paired-end reads, in order to elucidate the molecular breakpoints. In a two-step analysis, we first narrowed down the region by identifying discordant read-pairs, and then determined the precise molecular breakpoint by analysing the mapping locations of "soft-clipped" breakpoint-spanning reads. PCR and Sanger sequencing confirmed the identified breakpoints, both of which were located in intergenic regions. Significantly, the 7p15 breakpoint was located 523 kb upstream of HOXA13, the locus for hand-foot-genital syndrome. By inference from studies of HOXA locus control in the mouse, we suggest that the inversion has delocalised a HOXA13 enhancer to produce the phenotype observed in our patient. This study demonstrates how modern genetic diagnostic approach can characterise structural variants at nucleotide resolution and provide potential insights into functional regulation

Robust diagnostic genetic testing using solution capture enrichment and a novel variant-filtering interface.

Targeted hybridization enrichment prior to next-generation sequencing is a widespread method for characterizing sequence variation in a research setting, and is being adopted by diagnostic laboratories. However, the number of variants identified can overwhelm clinical laboratories with strict time constraints, the final interpretation of likely pathogenicity being a particular bottleneck. To address this, we have developed an approach in which, after automatic variant calling on a standard unix pipeline, subsequent variant filtering is performed interactively, using AgileExomeFilter and AgilePindelFilter (http://dna.leeds.ac.uk/agile), tools designed for clinical scientists with standard desktop computers. To demonstrate the method's diagnostic efficacy, we tested 128 patients using (1) a targeted capture of 36 cancer-predisposing genes or (2) whole-exome capture for diagnosis of the genetically heterogeneous disorder primary ciliary dyskinesia (PCD). In the cancer cohort, complete concordance with previous diagnostic data was achieved across 793 variant genotypes. A high yield (42%) was also achieved for exome-based PCD diagnosis, underscoring the scalability of our method. Simple adjustments to the variant filtering parameters further allowed the identification of a homozygous truncating mutation in a presumptive new PCD gene, DNAH8. These tools should allow diagnostic laboratories to expand their testing portfolios flexibly, using a standard set of reagents and techniques

Identification of a novel MAGT1 mutation supports a diagnosis of XMEN disease

XMEN (X-linked immunodeficiency with magnesium defect) is caused by loss-of-function mutations in MAGT1 which is encoded on the X chromosome. The disorder is characterised by CD4 lymphopenia, severe chronic viral infections and defective T-lymphocyte activation. XMEN patients are susceptible to Epstein-Barr virus infections and persistently low levels of intracellular Mg2+. Here we describe a patient that presented with multiple recurrent infections and a subsequent diffuse B-cell lymphoma. Molecular genetic analysis by exome sequencing identified a novel hemizygous MAGT1 nonsense mutation c.1005T>A (NM_032121.5) p.(Cys335*), confirming a diagnosis of XMEN deficiency. Follow-up immunophenotyping was performed by antibody staining and flow cytometry; proliferation was determined by 3H-thymidine uptake after activation by PHA and anti-CD3. Cytotoxic natural killer cell activity was assessed with K562 target cells using the NKTESTTM assay. While lymphocyte populations were superficially intact, B cells were largely naive with a reduced memory cell compartment. Translated NKG2D was absent on both NK and T cells in the proband, and normally expressed in the carrier mother. In vitro NK cell activity was intact in both the proband and his mother. This report adds to the growing number of identified XMEN cases, raising awareness of a, still rare, X-linked immunodeficiency

OVA: Integrating molecular and physical phenotype data from multiple biomedical domain ontologies with variant filtering for enhanced variant prioritization

Motivation: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. Results: Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype. We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool