Truck Traffic and Load Spectra of Indiana Roadways for the Mechanistic-Empirical Pavement Design Guide

The Mechanistic-Empirical Pavement Design Guide (MEPDG) has been employed for pavement design by the Indiana Department of Transportation (INDOT) since 2009 and has generated efficient pavement designs with a lower cost. It has been demonstrated that the success of MEPDG implementation depends largely on a high level of accuracy associated with the information supplied as design inputs. Vehicular traffic loading is one of the key factors that may cause not only pavement structural failures, such as fatigue cracking and rutting, but also functional surface distresses, including friction and smoothness. In particular, truck load spectra play a critical role in all aspects of the pavement structure design. Inaccurate traffic information will yield an incorrect estimate of pavement thickness, which can either make the pavement fail prematurely in the case of under-designed thickness or increase construction cost in the case of over-designed thickness. The primary objective of this study was to update the traffic design input module, and thus to improve the current INDOT pavement design procedures. Efforts were made to reclassify truck traffic categories to accurately account for the specific axle load spectra on two-lane roads with low truck traffic and interstate routes with very high truck traffic. The traffic input module was updated with the most recent data to better reflect the axle load spectra for pavement design. Vehicle platoons were analyzed to better understand the truck traffic characteristics. The unclassified vehicles by traffic recording devices were examined and analyzed to identify possible causes of the inaccurate data collection. Bus traffic in the Indiana urban areas was investigated to provide additional information for highway engineers with respect to city streets as well as highway sections passing through urban areas. New equivalent single axle load (ESAL) values were determined based on the updated traffic data. In addition, a truck traffic data repository and visualization model and a TABLEAU interactive visualization dashboard model were developed for easy access, view, storage, and analysis of MEPDG related traffic data

Multimodality Therapies for Localized Prostate Cancer.

PURPOSE OF REVIEW: Multimodality therapy including radical prostatectomy, radiation therapy, and hormone therapy are frequently deployed in the management of localized prostate cancer. We sought to perform a critical appraisal of the most contemporary literature focusing on the multimodality management of localized prostate cancer. RECENT FINDINGS: Men who are ideal candidates for multimodality therapy include those with unfavorable intermediate-risk disease, high-risk disease, and very high-risk disease. Enhancements in both systemic agents (including second-generation antiandrogens) as well as localized therapies (such as stereotactic body radiotherapy and brachytherapy) are refining the optimal balance between the use of systemic and local therapies for localized prostate cancer. Genomic predictors are emerging as critical tools for more precisely allocating treatment intensification with multimodality therapies as well as treatment de-intensification. Close collaboration among medical oncologists, surgeons, and radiation oncologists will be critical for coordinating evidence-based multimodality therapies when clearly indicated and for supporting shared decision-making in areas where the evidence is mixed

Impact of the COVID-19 Pandemic on Patient Preferences and Decision Making for Symptomatic Urolithiasis

Background: Pandemic restrictions have changed how patients approach symptomatic kidney stones. We used a mixed-methods digital ethnographic approach to evaluate social media discussions about patient concerns and preferences for urolithiasis care during the COVID-19 pandemic. Materials and Methods: We retrospectively analyzed kidney stone-related discussions on a large social media platform using qualitative analysis and natural language processing-based sentiment analysis. Posts were mined for demographic details, treatments pursued, and health care encounters. Pre-COVID-19 (January 1, 2020-February 29, 2020) and COVID-19 (March 1, 2020-June 1, 2020) posts were extracted from the popular online Reddit discussion board, r/KidneyStones, which is dedicated to discussions related to urolithiasis. Results: We extracted n = 649 posts (250 pre-COVID-19, 399 COVID-19); 150 from each cohort underwent thematic analysis and data extraction. Quantitative sentiment analysis was performed on 418 posts (179 pre-COVID-19, 239 COVID-19) that described stone-related decision making before intervention. Notable discussion themes during COVID-19 focused on barriers to care and concerns about stone management. Discussants exhibited more negative and anxious tones during COVID-19, based on sentiment analysis (p \u3c 0.01). Patient preferences shifted away from in-person visits and procedures (p \u3c 0.001). Mean reported stone size among those visiting emergency room (ER) increased from 5.1 to 10.5 mm (p \u3c 0.001). The proportion of discussants preferring conservative management with stones ≥10 mm increased (12.5% pre-COVID-19 vs 26% during COVID-19, p = 0.002). Opioid mentions increased from 9% to 27% of posts (p \u3c 0.001) and were most associated with conservative management discussions. Conclusions: Online discussion forums provide contemporaneous insight into patients\u27 experiences during a time when traditional patient-centered research methodologies are limited due to social distancing. During the pandemic, patients with symptomatic kidney stones expressed anxiety regarding outpatient encounters and reluctance toward procedural intervention. Patients opted instead for at-home conservative treatment beyond clinical guidelines and reserved ER visits for larger stones, potentially causing self-harm. Opioid discussions proliferated, an alarming consequence of the pandemic

S6K-STING interaction regulates cytosolic DNA-mediated activation of the transcription factor IRF3

Cytosolic DNA-mediated activation of the transcription factor IRF3 is a key event in host antiviral responses. Here we found that infection with DNA viruses induced interaction of the metabolic checkpoint kinase mTOR downstream effector and kinase S6K1 and the signaling adaptor STING in a manner dependent on the DNA sensor cGAS. We further demonstrated that the kinase domain, but not the kinase function, of S6K1 was required for the S6K1-STING interaction and that the TBK1 critically promoted this process. The formation of a tripartite S6K1-STING-TBK1 complex was necessary for the activation of IRF3, and disruption of this signaling axis impaired the early-phase expression of IRF3 target genes and the induction of T cell responses and mucosal antiviral immunity. Thus, our results have uncovered a fundamental regulatory mechanism for the activation of IRF3 in the cytosolic DNA pathway

Unprecedented Ambient Sulfur Trioxide (SO3) Detection : Possible Formation Mechanism and Atmospheric Implications

Sulfur trioxide (SO3) is a crucial compound for atmospheric sulfuric acid (H2SO4) formation, acid rain formation, and other atmospheric physicochemical processes. During the daytime, SO3 is mainly produced from the photo-oxidation of SO2 by OH radicals. However, the sources of SO3 during the early morning and night, when OH radicals are scarce, are not fully understood. We report results from two field measurements in urban Beijing during winter and summer 2019, using a nitrate-CI-APi-LTOF (chemical ionization-atmospheric pressure interface-long-time-offlight) mass spectrometer to detect atmospheric SO3 and H2SO4. Our results show the level of SO3 was higher during the winter than during the summer, with high SO3 levels observed especially during the early morning (similar to 05:00 to similar to 08:30) and night (similar to 18:00 to similar to 05:00 the next day). On the basis of analysis of SO2, NOx, black carbon, traffic flow, and atmospheric ions, we suggest SO3 could be formed from the catalytic oxidation of SO2 on the surface of traffic-related black carbon. This previously unidentified SO3 source results in significant H2SO4 formation in the early morning and thus promotes sub-2.5 nm particle formation. These findings will help in understanding urban SO3 and formulating policies to mitigate secondary particle formation in Chinese megacities.Peer reviewe

Is reducing new particle formation a plausible solution to mitigate particulate air pollution in Beijing and other Chinese megacities?

Atmospheric gas-to-particle conversion is a crucial or even dominant contributor to haze formation in Chinese megacities in terms of aerosol number, surface area and mass. Based on our comprehensive observations in Beijing during 15 January 2018-31 March 2019, we are able to show that 80-90% of the aerosol mass (PM2.5) was formed via atmospheric reactions during the haze days and over 65% of the number concentration of haze particles resulted from new particle formation (NPF). Furthermore, the haze formation was faster when the subsequent growth of newly formed particles was enhanced. Our findings suggest that in practice almost all present-day haze episodes originate from NPF, mainly since the direct emission of primary particles in Beijing has considerably decreased during recent years. We also show that reducing the subsequent growth rate of freshly formed particles by a factor of 3-5 would delay the buildup of haze episodes by 1-3 days. Actually, this delay would decrease the length of each haze episode, so that the number of annual haze days could be approximately halved. Such improvement in air quality can be achieved with targeted reduction of gas-phase precursors for NPF, mainly dimethyl amine and ammonia, and further reductions of SO2 emissions. Furthermore, reduction of anthropogenic organic and inorganic precursor emissions would slow down the growth rate of newly-formed particles and consequently reduce the haze formation.Peer reviewe

IgG and fibrinogen driven nanoparticle aggregation

A thorough understanding of how proteins induce nanoparticle (NP) aggregation is crucial when designing in vitro and in vivo assays and interpreting experimental results. This knowledge is also crucial when developing nano-applications and formulation for drug delivery systems. In this study, we found that extraction of immunoglobulin G (IgG) from cow serum results in lower polystyrene NPs aggregation. Moreover, addition of isolated IgG or fibrinogen to fetal cow serum enhanced this aggregation, thus demonstrating that these factors are major drivers of NP aggregation in serum. Counter-intuitively, NP aggregation was inversely dependent on protein concentration; i.e., low protein concentrations induced large aggregates, whereas high protein concentrations induced small aggregates. Protein-induced NP aggregation and aggregate size were monitored by absorbance at 400 nm and dynamic light scattering, respectively. Here, we propose a mechanism behind the protein concentration dependent aggregation; this mechanism involves the effects of multiple protein interactions on the NP surface, surface area limitations, aggregation kinetics, and the influence of other serum proteins.We thank Professor Sara Linse for scientific discussions and advice and Professor Patrik Brundin for enabling access to the light microscope. The project received financial support from Nanometer structure consortium at Lund University (nmC@LU), Lars Hierta Foundation, and the research school FLAK of Lund University