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The Shawan River will be the focal point in the development of the Panyu District, the southernmost district of Guangzhou City in the Guangdong Province of South China. In this research, through the use of two scenarios, the future water quality of the Shawan River was predicted with relation to changes in the water quantity utilized to fuel industrial and domestic development. The worst-case scenario used, simulated the situation if no wastewater treatment was employed, and the best-case scenario simulated the situation if 90% of the pollution load was removed. The period of simulation was for the years 2020 and 2050. Three flowrates were used in the evaluation, those of: the 90% probability of the month of lowest flow (37.2 m³/s); and the range of flowrates within the low flow period, that is, the dry season from November to February (307 and 432 m³/s). Subsequently, two countermeasures (industrial and domestic water savings) -- sustainable initiatives -- were nested within the two scenarios to ascertain improvements in water quality as a direct result of reduction in water quantity used. The industrial water saving countermeasure showed the greatest improvement in water quality. For the 90% probability of lowest flow for the worst-case scenario, this countermeasure equated to a 63% decrease in BOD. For the low flow period flowrates the background concentration of pollutants was more influential than improvements imparted by the countermeasures to the future predicted water quality. It was recommended that industrial countermeasures be used that take into account water saving, water recycling, the use of brackish water for cooling, and the implementation of economic pricing initiatives. Also that inter-district governmental policy initiatives be introduced to prevent upstream pollution from influencing downstream proposals, further enhancing sustainable water management of the Shawan River. [ABSTRACT FROM AUTHOR]

Background Individual patient data from two multicentre, randomised trials comparing atezolizumab with docetaxel in previously treated advanced non-small-cell lung cancer (NSCLC) were analyzed to identify any preferable therapeutic approaches for patient subsets stratified by EGFR mutation status. Methods We pooled 1,137 patients from the phase II POPLAR trial (NCT01903993) and the phase III OAK trial (NCT02008227). Patients were randomly assigned to receive either atezolizumab or docetaxel and were analyzed based on stratification of EGFR mutation status. We built a novel algorithm integrating the blood-based tumor mutation burden and the ctDNA maximum somatic allele frequency (bTMB-MSAF score) and developed a novel clinicopathologic-genomic nomogram to predict individual survival. Results In the whole intention-to-treat population, OS was significantly longer with atezolizumab than with docetaxel (hazard ratio [HR] 0.72, P < 0.001). Among patients without EGFR or ALK mutations, overall survival (OS) was significantly longer with atezolizumab than with docetaxel (HR 0.67; P < 0.001); patients with a bTMB-MSAF score<20 showed improvement in OS (HR 0.56; P < 0.001) and progression-free survival (PFS) (HR 0.74; P = 0.0023), and these patients who concurrently had programmed death ligand 1 (PD-L1) expressing on over 50% tumor cells or over 10% of tumor-infiltrating immune cells (TC3 or IC3) had the greatest OS improvements (HR 0.44; P = 0.007) and promising PFS benefits (HR 0.54; P = 0.019). EGFR mutant patients could not gain significant OS or PFS benefits from atezolizumab over docetaxel, irrespective of PD-L1 expression and bTMB-MSAF score. Patients with low-risk scores had longer OS (HR 0.17; P < 0.001; AUC=0.912 for 3-year OS) than patients with high-risk scores classified by the nomogram. Conclusions Atezolizumab showed better OS and PFS than docetaxel in previously treated EGFR wild-type NSCLC patients with a bTMB-MSAF score < 20, especially in those with PD-L1 expression of TC3 or IC3. Our clinicopathologic-genomic nomogram is effective in predicting survival of NSCLC patients undergoing atezolizumab. Clinical trial identification NCT01903993 and NCT02008227. Legal entity responsible for the study Herui Yao. Funding Herui Yao is funded by the National Science and Technology Major Project under Grant [2020ZX09201021]; National Natural Science Foundation of China under Grant [81372819, 81572596, U1601223]; Natural Science Foundation of Guangdong Province under Grant [2017A030313828]; and Guangzhou Science and Technology Program under Grant [201704020131]. Disclosure All authors have declared no conflicts of interest. [ABSTRACT FROM AUTHOR]