Renal cell carcinoma with tumor thrombus: A review of relevant anatomy and surgical techniques for the general urologist.

Renal cell carcinoma (RCC) is estimated to account for 4.1% of all new cancer diagnoses and 2.4% of all cancer deaths in 2020 according to the National Cancer Institute SEER database. This will likely total 73,000 new cases and 15,000 deaths. RCC is one of the most lethal of the common cancers urologists will encounter with a 5-year relative survival of 75.2%. Renal cell carcinoma is one of a small subset of malignancies that are associated with tumor thrombus formation, which is tumor extension into a blood vessel. An estimated 4% to 10% of patients with RCC will have some degree of tumor thrombus extending into the renal vein or inferior vena cava at the time of diagnosis. Tumor thrombi change the staging of RCC and therefore are an important part of initial patient workup. It is known that such tumors are more aggressive with higher Fuhrman grades, N+ or M+ at time of surgery and have higher probability of recurrence with lower cancer-specific survival. Aggressive surgical intervention with radical nephrectomy and thrombectomy can be performed with survival benefits. Classifying the level of the tumor thrombus becomes vitally important in surgical planning as it will dictate the surgical approach. Level 0 thrombi may be amenable to simple renal vein ligation while level 4 can require thoracotomy and possible open-heart surgery with coordination of many surgical teams. Here we will review the anatomy associated with each level of tumor thrombus and attempt to construct an outline for surgical techniques that may be used. We aim to give a concise overview so that general urologists may use it to understand these potentially complicated cases.

Operational bias correction for PM2.5 using the AIRPACT air quality forecast system in the Pacific Northwest.

A bias correction scheme based on a Kalman filter (KF) method has been developed and implemented for the AIRPACT air quality forecast system which operates daily for the Pacific Northwest. The KF method was used to correct hourly rolling 24-h average PM2.5 concentrations forecast at each monitoring site within the AIRPACT domain and the corrected forecasts were evaluated using observed daily PM2.5 24-h average concentrations from 2017 to 2018. The evaluation showed that the KF method reduced mean daily bias from approximately -50% to ±6% on a monthly averaged basis, and the corrected results also exhibited much smaller mean absolute errors typically less than 20%. These improvements were also apparent for the top 10 worst PM2.5 days during the 2017-2018 test period, including months with intensive wildfire events. Significant differences in AIRPACT performance among urban, suburban, and rural monitoring sites were greatly reduced in the KF bias correction forecasts. The daily 24-h average bias corrections for each monitoring site were interpolated to model grid points using three different interpolation schemes: cubic spline, Gaussian Kriging, and linear Kriging. The interpolated results were more accurate than the original AIRPACT forecasts, and both Kriging methods were better than the cubic spline method. The Gaussian method yielded smaller mean biases and the linear method yielded smaller absolute errors. The KF bias correction method has been implemented operationally using both Kriging interpolation methods for routine output on the AIRPACT website (http://lar.wsu.edu/airpact). This method is relatively easy to implement, but very effective to improve air quality forecast performance.Implications: Current chemical transport models, including CMAQ, used for air quality forecasting can have large errors and uncertainties in simulated PM2.5 concentrations. In this paper, we describe a relatively simple bias correction scheme applied to the AIRPACT air quality forecast system for the Pacific Northwest. The bias correction yields much more accurate and reliable PM2.5 results compared to the normal forecast system. As such, the operational bias corrected forecasts will provide a much better basis for daily air quality management by agencies within the region. The bias corrected results also highlight issues to guide further improvements to the normal forecast system.

Impacts of prescribed fires and benefits from their reduction for air quality, health and visibility in the Pacific Northwest of the United States.

Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and local air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios - 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho and western Montana where most prescribed fires occur. Prescribed burning contributes to visibility impairment and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 work day losses can be attributed to prescribed fires and these health impacts decrease by 25-30% when a 30% fire emission scenario is considered. Implications This study assesses the potential regional and local air quality, public health and visibility impacts from prescribed burning activities as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts and improved visibility.

Altered gene expression patterns in intrauterine growth restriction: potential role of hypoxia.

OBJECTIVE: Placental insufficiency is a primary cause of intrauterine growth restriction (IUGR). In our study, microarray technology was used to identify genes, which may impair placentation resulting in IUGR. STUDY DESIGN: The RNA was isolated from both IUGR term placentas and normal term placentas. Microarray experiments were used to identify differentially expressed genes between the 2 cohorts. Real-time quantitative reverse transcriptase polymerase chain reaction and immunohistochemistry were used in follow-up experiments. RESULTS: Microarray experiments identified increased expression of certain genes including leptin, soluble vascular endothelial growth factor receptor, human chorionic gonadotropin, follistatin-like 3, and hypoxia-inducible factor 2alpha in the IUGR. Real-time quantitative polymerase chain reaction confirmed these results. CONCLUSION: The upregulation of soluble vascular endothelial growth factor receptor and hypoxia-inducible factor 2alpha at this period in pregnancy indicate that placental angiogenesis is altered in IUGR and that hypoxia is a major contributor to maldevelopment of the placental vasculature.