SensorMetrix (United States)

Intersections are critical elements of roadway infrastructure, often characterized by high levels of congestion and potential for severe crashes. To address increasing congestion and safety concerns, transportation agencies have begun implementing innovative geometric designs such as alternative intersections. These designs have also been called innovative intersections. This paper presents findings that evaluated the change in queue lengths of alternative intersections before and after their construction. The study involved multiple sites where alternative intersections were recently constructed, with data collected before construction and after completion. The key metric for this paper was queue lengths, with data collected using extensive video recording setups. For the two sites in Arizona with median U-turns (MUTs), the queues for the major road through movements were reduced even with an increase in volume. The signalized restricted crossing U-turn in Minnesota, the displaced left-turn (DLT) in Texas and in Virginia, and the hybrid intersection (mix of DLTs and MUTs) in Virginia all experienced improvements in queue lengths after construction of the alternative intersection. The analysis revealed that alternative intersections result in shorter vehicle queues and improved traffic flow compared to conventional designs.

Abstract The MYC gene, with its oncogenic potential, has long been a formidable challenge in conventional drug discovery efforts, and its critical role in cancer progression and resistance has underscored the need for innovative therapeutic strategies. Here we demonstrate the capabilities of the Ribometrix RNA-targeting platform to modulate the c-MYC mRNA with small molecules with the aim of reducing c-MYC protein levels. Using our comprehensive platform of RNA-targeting drug discovery tools and analyses including chemical probing, structure modeling, high-purity RNA production, high-throughput screening, and biophysical characterization, we evaluated the potential to directly target c-MYC mRNA using small molecules. Our analysis revealed six high-confidence structured elements throughout the c-MYC mRNA expected to harbor tertiary structures amenable to drug-like ligand binding. Leveraging the multifaceted chemical probing and structure modeling components of our platform, we confirmed that our in vitro-transcribed RNA screening constructs adopt the same structures found in endogenous cellular c-MYC transcripts. After large-scale in vitro RNA preparation, we subjected four of these RNA elements to high-throughput screens of chemically diverse drug-like libraries using mass spectrometry affinity-selection that identified multiple chemical series with sub-micromolar affinity. We validated binding affinity using orthogonal methods including isothermal titration calorimetry and NMR. To eliminate pan-binding ligands, we evaluated of selectivity against a panel of non-target mRNA structures. Importantly, these compounds lead to rapid (4 hr) reduction of MYC protein levels in a small cell lung cancer cell line, DMS-273, with no cellular toxicity at 72 hr suggesting an on-target effect. Employing our suite of chemical probing tools, we confirmed that compounds from multiple series engage the c-MYC mRNA in cells. Medicinal chemistry efforts are ongoing to increase potency and define the precise mechanism of action in clinically relevant models. The discovery of these c-MYC mRNA-binding small molecules not only validates the utility of the Ribometrix RNA-targeted small molecule discovery platform but also showcases its potential in tackling traditionally 'undruggable' targets and provides a promising avenue for developing novel anti-cancer therapies. As we learn more about the intricacies of c-MYC mRNA biology and further refine effective small molecules, our results provide practical insights into previously-unknown vulnerabilities of MYC and present tangible opportunities for advancing targeted cancer therapies. Citation Format: Matthew J. Smola, Krista Marran, Sarah E. Thompson, Brittani Patterson, Roheeth K. Pavana, Caleb Sutherland, Jessica A. Sorrentino, Katherine D. Warner. Leveraging an RNA-targeting platform for the discovery of cell-active c-MYC mRNA-binding small molecules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 680.

BackgroundIn Latin America, substance related disorders are highly prevalent and one of the treatment strategies is the Therapeutic Communities (TCs), however, in Latin America there is scarce data about this treatment strategies, their quality, drop-out rates and patient satisfaction.MethodsBased on a previous study in 5 Latin American countries, the TCs who had a score equal or higher than 9 according to the De Leon criteria which are some fundamental items that the TCs should meet, were selected to carry out a descriptive and retrospective study of qualitative and quantitative characteristics of the TCs.ResultsData from 58 TCs in 5 countries were included, with a sample of 1414 patients interviewed, of which most were single men, with no hospitalization history in a therapeutic community. Marijuana was the most commonly substance used in the 30 days prior to hospitalization, with 78% of interviewees referring alcohol consumption in the last 6 months and an average onset of psychoactive substances at 16 years of age. A 79% of the patients interviewed perceived some improvement during their stay in the TCs. The less fulfilled Quality Indicators by the TCs were “Requesting a professional qualification to former addicts that belonged to the program” and “Work as part of the therapeutic program”. Among the reasons for discharge found in the database, 44% were due to therapeutic discharge with fulfillment of the treatment plan and 44% withdraws.ConclusionThe user satisfaction with TCs, in terms of infrastructure and quality are quite high, as the fulfillment of essential quality items, however, the follow up information to evaluate effectiveness of the treatment is poor or in some cases unknown.

While it is increasingly being recognized that biotic ligand models (BLMs) are valuable in the risk assessment of metals in aquatic systems, the development of chronic BLMs has been less advanced for lead than for other metals. The authors investigated the univariate effects of Ca and pH on the chronic reproductive toxicity of Pb to Ceriodaphnia dubia at 4 levels. Calcium influenced chronic Pb toxicity to C. dubia only to a relatively small extent, whereas a high pH (8.2) provided strong protection against Pb toxicity (compared with lower pH levels). Based on this data set, a chronic Pb BLM for C. dubia was developed. The effect of pH was modeled as a single biotic ligand site competition by H(+) with a log stability constant for binding of H(+) to the biotic ligand (K(HBL)) of 7.6, while no other competitive constants were needed. The developed BLM was shown, in an independent validation with 3 other data sets, to be capable of predicting chronic Pb toxicity to different clones of C. dubia by an error of less than a factor of 2 in most synthetic and natural waters considered. The results add to the growing evidence that BLM-based risk assessment or water-quality criteria for Pb are likely to be more appropriate relative to hardness-based assessments or criteria.

The U.S. Army Corps of Engineers Albuquerque District, in collaboration with various local partners, has been implementing restoration projects in the Albuquerque Reach of the Middle Rio Grande. These projects have included the removal of the metal jetty jacks, debris, and dense thickets of non-native vegetation (salt cedar, Russian olive, and Siberian elm) that occur in the bosque (riparian forest), creation of wet habitats (such as willow swales and high-flow channels), and revegetation schemes focused on increasing the diversity and quality of wildlife habitat. The goal of many of these projects is to develop a framework to restore the bosque into a more functional and sustainable ecosystem. Projects implemented on the ground are being monitored for various restoration success components – such as vegetation response, wildlife use and response, and surface water-ground water interaction. This monitoring has provided important information in regards to planning future restoration efforts that meet all project objectives. Monitoring has also pointed out where improvement is needed and adaptive management can be implemented. This presentation will give an overview of the various projects and monitoring that has taken place and how information gained has been beneficial.

P lanetizen: Contemporary Debates in Urban Planning is organized around ideas or topics that have been explored on Planetizen, an online community, and is organized into five sections: “Sprawl vs. ...

Watersheds have historically been used as the appropriate spatial classification unit for managing water resources. However, geology, soil type, predominant vegetation, and climate have obvious influences on water quality and are not constrained by watercourses or political boundaries. This concept has evolved for several decades and developed the concept of ecoregions and other spatial schemes. While this approach to water resource management has considered the interaction between water quality and biological integrity (aquatic community structure and assemblage), it has not been applied in the context of predicting aquatic toxicity. As such, a previously published study providing a chemical and toxicological data set consisting of 24 sampling sites in South Carolina, USA, and was used to develop empirical models for predicting acute copper (Cu) toxicity to larval fathead minnows (Pimephales promelas). Moreover, numerous spatial classifications (hydrologic units, ecoregions, stream order, adjacent land use, and proximity to certain land uses) and seasonality were used to delineate sites and develop empirical models based on these different classifications. An independent sampling and testing regime was implemented to determine the performance of the empirical models and whether certain classifications could be used to extrapolate toxicity data across spatial landscapes. Additionally, a computational model (biotic ligand model [BLM]) for deriving site-specific water quality criteria for Cu also was used as a reference for current regulatory application. Empirical models based on delineations of stream order, hydrologic unit, and downstream distance to urbanization accurately predicted at least 60% of the observed Cu toxicity values within the supplemental data set. Delineations based on adjacent land use, ecoregions, and seasons were not as useful for predicting acute Cu toxicity but demonstrated better performance than the BLM.