Interacting Semantic Systems: Mixtec Expressions of Location

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Argument Forms in Lexical Semantics

Proceedings of the Twelfth Annual Meeting of the Berkeley Linguistics Society (1986), pp. 442-45

Knockout of the Arp2/3 complex in epidermis causes a psoriasis-like disease hallmarked by hyperactivation of transcription factor Nrf2

Arp2/3 complex assembles branched actin filaments key to many cellular processes, but its organismal roles remain poorly understood. Here we employed conditional arpc4 knockout mice to study the function of the Arp2/3 complex in the epidermis. We found that depletion of the Arp2/3 complex by knockout of arpc4 results in skin abnormalities at birth that evolve into a severe psoriasis-like disease hallmarked by hyperactivation of transcription factor Nrf2. Knockout of arpc4 in cultured keratinocytes was sufficient to induce nuclear accumulation of Nrf2, upregulation of Nrf2-target genes and decreased filamentous actin levels. Furthermore, pharmacological inhibition of the Arp2/3 complex unmasked the role of branched actin filaments in Nrf2 regulation. Consistently, we unveiled that Nrf2 associates with the actin cytoskeleton in cells and binds to filamentous actin in vitro. Finally, we discovered that Arpc4 is downregulated in both human and mouse psoriatic epidermis. Thus, the Arp2/3 complex affects keratinocytes' shape and transcriptome through an actin-based cell-autonomous mechanism that influences epidermal morphogenesis and homeostasis

Gammaretrovirus-mediated correction of SCID-X1 is associated with skewed vector integration site distribution in vivo

We treated 10 children with X-linked SCID (SCID-X1) using gammaretrovirus-mediated gene transfer. Those with sufficient follow-up were found to have recovered substantial immunity in the absence of any serious adverse events up to 5 years after treatment. To determine the influence of vector integration on lymphoid reconstitution, we compared retroviral integration sites (RISs) from peripheral blood CD3(+) T lymphocytes of 5 patients taken between 9 and 30 months after transplantation with transduced CD34(+) progenitor cells derived from 1 further patient and I healthy donor. Integration occurred preferentially in gene regions on either side of transcription start sites, was clustered, and correlated with the expression level in CD34(+) progenitors during transduction. In contrast to those in CD34(+) cells, RISs recovered from engrafted CD3(+)T cells were significantly overrepresented within or near genes encoding proteins with kinase or transferase activity or involved in phosphorus metabolism. Although gross patterns of gene expression were unchanged in transduced cells, the divergence of RIS target frequency between transduced progenitor cells and post-thymic T lymphocytes indicates that vector integration influences cell survival, engraftment, or proliferation

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Introduction to : Special Issue: Neural Networks and Machine Learning for Natural Language Processing [editorial]

The rapid increase of information available on the Internet, much of it textual, calls for computational methods that efficiently organise and classify natural language documents and allow for automatic language acquisition. The last years have seen an increase in conferences, workshops, research degree programs and commercial activities in this area. While the application of neural networks and machine learning techniques to natural language processing is not a recent development, the renewed interest is driven by the need to manage the information explosion of the Internet. A number of new fields, such as Web- and text mining, audio mining and topic detection and tracking\ud (TDT) have emerged and long established areas such as information retrieval and extraction are more relevant than ever.\ud \ud This special issue includes articles which address a number of core questions, including the investigation of the underlying theoretical foundations of machine learning, the implementation and evaluation of methods for learning natural language with neural networks or other machine learning approaches, and applications of such learning systems in various domains