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Melatonin and it is derivative affect cancers stem-like phenotypes associated with carcinoma of the lung tissues via AKT downregulation.
In XRD studies, the shift in diffracted peak's position reveals the increased proportion of Co ions. Further, EDX results also confirm the same with the characteristic peaks. Finally, compared to the other methods, the corrosion resistance was more efficient in the US-SC-CO2 process by 73.75%.
Previous studies describe a large variation in the proportion of patients undergoing treatment with curative intent for esophageal (EC) and gastric cancer (GC). Since centralization of surgical care was initiated and more awareness regarding hospital practice variation was potentially present, we hypothesized that hospital practice variation for potentially curable EC and GC patients changed over time.

Patients with potentially curable EC (n = 10,115) or GC (n = 3988) diagnosed between 2012-2017 were selected from the Netherlands Cancer Registry. Multilevel multivariable logistic regression was used to analyze the differences in the probability of treatment with curative intent between hospitals of diagnosis over time, comparing 2012-2014 with 2015-2017. Relative survival (RS) between hospitals with different probabilities of treatment with curative intent were compared.

The range of proportions of patients undergoing treatment with curative intent per hospital of diagnosis for EC was 45-95 % in 2012-2014 and 54-89 % in 2015-2017, and for GC 52-100 % and 45-100 %. The adjusted variation declined for EC with Odds Ratios ranging from 0.50 to 1.72 between centers in the first period to 0.70-1.44 in the second period (p < 0.001) and did not change for GC (Odds Ratios ranging from 0.78 to 1.23 to 0.82-1.23, (p = 1.00)). A higher probability of treatment with curative intent was associated with a better survival for both malignancies.

Although substantial variation between hospitals of diagnosis in the probability in receiving treatment with curative intent still exists for both malignancies, it has decreased for EC. A low probability of receiving curative treatment remained associated with worse survival.
Although substantial variation between hospitals of diagnosis in the probability in receiving treatment with curative intent still exists for both malignancies, it has decreased for EC. A low probability of receiving curative treatment remained associated with worse survival.Safety Performance Functions (SPFs) have been widely used by researchers and practitioners to conduct roadway safety evaluation. Traditional SPFs are usually developed by using annual average daily traffic (AADT) along with geometric characteristics. However, the high level of aggregation may lead to a failure to capture the temporal variation in traffic characteristics (e.g., traffic volume and speed) and crash frequencies. In this study, SPFs at different aggregation levels were developed based on microscopic traffic detector data from California, Florida, and Virginia. More specifically, five aggregation levels were considered (1) annual average weekday hourly traffic (AAWDHT), (2) annual average weekend hourly traffic (AAWEHT), (3) annual average weekday peak/off-peak traffic (AAWDPT), (4) annual average day of the week traffic (AADOWT), and (5) annual average daily traffic (AADT). Harmine Model estimation results showed that the segment length and volume, as exposure variables, are significant across all the aggregation levels. Average speed is significant with a negative coefficient, and the standard deviation of speed was found to be positively associated with the crash frequency. It is noteworthy that the operation of the high occupancy vehicle (HOV) lanes was found to have a positive effect on crash frequency across all the aggregation levels. The model results also showed that the AAWDPT and AADOWT models consistently performed better (the improvements range from 3.14%-16.20%) than the AADT-based SPF, which implies that the differences between the day of the week and peak/off-peak periods should be considered in the development of crash prediction models. The model transferability results indicated that the SPFs between Florida and Virginia are transferrable, while the models between California and the other two states are not transferrable.Cannabis use is increasing in the U.S. Driving under the influence of cannabis (DUIC) may be increasing as well potentially resulting in fatal and serious injury crashes. The purpose of this article is to explore the belief system associated with driving under the influence of cannabis (DUIC) using structural equation modeling (SEM). A sample (n = 2,084) of surveys collected from adults in the U.S. was analyzed using SEM to reveal the latent structure of the belief system associated with DUIC. The results of this analysis indicated that reported DUIC behavior (frequency and recency) was predicted by willingness that influenced intention. Willingness and intention were directly influenced by control beliefs, attitudes, norms, and attitudes (prototype image) toward people who never DUIC. Intention was also influenced by attitudes toward people who do DUIC. Intention had a stronger influence on DUIC than willingness alone. These components were influenced by underlying behavioral, normative, and control beliefs. Thus, strategies that can change these beliefs may also reduce DUIC.In road safety, a commonly-used measure of treatment effectiveness is the crash modification factor, usually defined as a ratio of the expected crash frequency with the treatment to the expected frequency without. This paper explores the possibility of using surrogates to estimate crash modification factors. As in other situations where observational data are used to estimate causal effects, it is necessary to leverage background causal knowledge with the observational results. When the background knowledge is such that a crash-generating mechanism can be represented with a directed acyclic graph, the connectivity structure of the graph can be used to identify candidate surrogates. The modification factor associated with a safety-related improvement can then, in principle, be estimated from knowledge of how the improvement affects the surrogates, together with information on how the surrogates are distributed in the population of crashes. After developing this relationship between surrogates and crash modification factors, its potential usefulness is illustrated with two simulation studies, where estimates of CMFs using surrogates are compared to estimates computed from crash frequencies.
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