Prostate cancer cell malignancy via modulation of HIF-1 alpha pathway with isoflurane and propofol alone and in combination

BACKGROUND: Surgery is considered to be the first line treatment for solid tumours. Recently, retrospective studies reported that general anaesthesia was associated with worse long-term cancer-free survival when compared with regional anaesthesia. This has important clinical implications; however, the mechanisms underlying those observations remain unclear. We aim to investigate the effect of anaesthetics isoflurane and propofol on prostate cancer malignancy. METHODS: Prostate cancer (PC3) cell line was exposed to commonly used anaesthetic isoflurane and propofol. Malignant potential was assessed through evaluation of expression level of hypoxia-inducible factor-1α (HIF-1α) and its downstream effectors, cell proliferation and migration as well as development of chemoresistance. RESULTS: We demonstrated that isoflurane, at a clinically relevant concentration induced upregulation of HIF-1α and its downstream effectors in PC3 cell line. Consequently, cancer cell characteristics associated with malignancy were enhanced, with an increase of proliferation and migration, as well as development of chemoresistance. Inhibition of HIF-1α neosynthesis through upper pathway blocking by a PI-3K-Akt inhibitor or HIF-1α siRNA abolished isoflurane-induced effects. In contrast, the intravenous anaesthetic propofol inhibited HIF-1α activation induced by hypoxia or CoCl(2). Propofol also prevented isoflurane-induced HIF-1α activation, and partially reduced cancer cell malignant activities. CONCLUSIONS: Our findings suggest that modulation of HIF-1α activity by anaesthetics may affect cancer recurrence following surgery. If our data were to be extrapolated to the clinical setting, isoflurane but not propofol should be avoided for use in cancer surgery. Further work involving in vivo models and clinical trials is urgently needed to determine the optimal anaesthetic regimen for cancer patients

Remoção de sulfato de águas residuárias industriais em reator anaeróbio de leito fixo operado em bateladas sequenciais Sulfate removal from industrial wastewaters in fixed film anaerobic sequential batch reactor

Avaliou-se o potencial de uso reator anaeróbio operado em bateladas seqüenciais com biomassa imobilizada (ASBBR), em escala piloto, no tratamento de água residuária industrial contendo elevadas concentrações de sulfato. O ASBBR, com volume total de 1.2 m³, foi preenchido com carvão mineral como meio suporte para imobilização da biomassa (leito fixo). Foram aplicadas cargas de 0,15; 0,30; 0,65; 1,30 e 1,90 kg SO4-2/ciclo (ou batelada) com duração de 48 h, correspondendo, respectivamente, às concentrações de sulfato no afluente de 0,25; 0,50; 1,0; 2,0 e 3,0 gSO4-2.l-1. Utilizou-se etanol como doador de elétrons para a redução do sulfato. O reator foi operado à temperatura ambiente (29&plusmn;8ºC), tendo sido obtidas eficiências médias na redução de sulfato entre 88 e 92% em 92 ciclos (275 dias). Os resultados obtidos permitem concluir que o uso de reatores ASBBR constitui-se em alternativa eficiente para a remoção de sulfatos de águas residuárias com características semelhantes às utilizadas neste trabalho.<br>The potential use of an anaerobic sequencing batch biofilm reactor (ASBBR) in pilot-scale for the treatment of a sulfate-rich industrial wastewater was evaluated. The pilot 1.2 m³ ASBBR reactor was filled with mineral coal for biomass immobilization (fixed film). The sulfate loading rates applied were 0.15; 0.30; 0.65; 1.30 and 1.90 kg SO4-2/cycle (or batch). Each cycle lasted 48 h. The influent concentrations were, respectively, 0.25; 0.50; 1.0; 2.0 and 3.0 gSO4-2.l-1. Ethanol was used as electron donor for sulfate reduction. The reactor operated at ambient temperature (29&plusmn;8ºC), and the mean efficiencies of sulfate removal were in the range 88 to 92% in the 92 run cycles. The total operating period comprised 275 days. Based on the results obtained in this research, it could be concluded that the ASBBR can be an efficient alternative for the removal of sulfate from other industrial wastewaters with similar characteristics

Water use indicators at farm scale: methodology and case study

Indicators for water use at farm scale can assist farmers in understanding the water flows on their farms and in optimizing water use by adapting agronomic measures and farm management. The objective of this work is to develop a methodology to estimate water flows at the farm scale, to derive indicators for farm water use, and to apply them in a first case study. After the spatial and temporal boundaries of the farm system and the water flows are defined, three indicators to assess water use at the farm scale are developed: farm water productivity, degree of water utilization, and specific inflow of technical water. Farm water productivity describes the ratio of farm output to water input, where the water input is the total of those water inflows into the farm system that can be assigned to the generation of farm output. Farm output is expressed on a mass basis, food energy basis, and monetary basis. The degree of water utilization characterizes the relationship between productive water to the total water inflow into the farm system, where productive water comprises those water flows that directly contribute to biomass generation via plant and animal metabolism. The specific technical water inflow quantifies the water inflow into the system by technical means relative to the farm area. The application of the methodology in a first case study for a mixed crop-livestock farm with 2869 ha in Germany results in a farm water productivity of 2.30 kg fresh mass per mWinput-3, 1.03 kg dry mass per m Winput-3, 5.96 GJ m Winput-3, and 0.25 € mWinput-3. The degree of water utilization is 0.56. The specific technical water inflow is 36.5 m3 ha-1 year -1. Factors that mainly effect these indicators and general approaches to optimize water use in farms are discussed as well as the further research required for practical implementation

Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients