Evolution of Modeled Cortisol Is Prognostic of Death in Hospitalized Patients With COVID-19 Syndrome.

Introduction: Patients hospitalized with SARS-CoV-2 have an elevated risk of mortality related to a severe inflammatory response. We hypothesized that biological modeling with a complete blood count (CBC) would be predictive of mortality. Method: In 2020, 81 patients were randomly selected from La Rochelle Hospital, France for a simple blinded retrospective study. Demographic, vital signs, CBC and CRP were obtained on admission, at days 2-3 and 3-5. From a CBC, two biological modeling indexes were resulted: the neutrophil-to-lymphocyte ratio (NLR) and cortisol index adjusted (CA). Results: By ANOVA, in survivors vs. non-survivors there was statistical different at p < 0.01 for age (66.2 vs. 80), CRP (92 vs. 179 mg/dL, normal < 10), cortisol index adjusted (323 vs. 698, normal 3-7) and genito-thyroid indexes (7.5 vs. 18.2, normal 1.5-2.5), and at p = 0.02 creatinine (1.03 vs. 1.48, normal 0.73-1.8 mg/dL). By mixed model analysis, CA and NLR improved in those who survived across all three time points, but worsened again after 3-5 days in non-survivors. CRP continued to improve over time in survivors and non-survivors. Positive vs. Negative predictive value were: CRP (91.1%, 30.4%), NLR (94.5%, 22.7%), CA (100%, 0%). Discussion: Cortisol modeling and the neutrophil-to-lymphocyte ratio were more accurate in describing the course of non-survivors than CRP. Conclusion: In patients admitted for SARS CoV-2 infection, biological modeling with a CBC predicted risk of death better than CRP. This approach is inexpensive and easily repeated.

Assessment of energy crops alternative to maize for biogas production in the Greater Region.

The biomethane yield of various energy crops, selected among potential alternatives to maize in the Greater Region, was assessed. The biomass yield, the volatile solids (VS) content and the biochemical methane potential (BMP) were measured to calculate the biomethane yield per hectare of all plant species. For all species, the dry matter biomass yield and the VS content were the main factors that influence, respectively, the biomethane yield and the BMP. Both values were predicted with good accuracy by linear regressions using the biomass yield and the VS as independent variable. The perennial crop miscanthus appeared to be the most promising alternative to maize when harvested as green matter in autumn and ensiled. Miscanthus reached a biomethane yield of 5.5 ± 1 × 10(3)m(3)ha(-1) during the second year after the establishment, as compared to 5.3 ± 1 × 10(3)m(3)ha(-1) for maize under similar crop conditions.

Chemical characteristics and biofuels potentials of various plant biomasses: influence of the harvesting date.

BACKGROUND: An optimal valorization of plant biomasses to produce biofuels requires a good knowledge of the available contents and molecular composition of the main chemical components, which changes with the harvesting date. Therefore, we assessed the influence of harvesting date on the chemical characteristics of various energy crops in the context of their conversion to biofuels. RESULTS: We showed that the biomass chemical composition, enzymatic digestible organic matter, bioethanol and thermal energy production potential for each species are impacted by the harvesting date. The proportion of enzymatically digestible organic matter decreases as the harvesting date is delayed. This is related to the increase in cellulose and lignin contents. The suitability of the biomasses for bioethanol production increases with harvest stage, as the total carbohydrates content increases. The suitability of the biomasses as a source of thermal energy increases according to the harvesting date as the proportion of organic matter increases and the content of mineral compounds decreases. For all investigated energy conversions, the best harvesting period is autumn, because the significantly higher crop dry matter yield largely compensates for the sometimes slightly less favorable chemical characteristics. CONCLUSION: While the biomass composition of energy crops changes with harvest stage, the dry biomass yield per unit area is the main factor that controls the total amount of chemical components, digestible organic matter, bioethanol and thermal energy that can be expected to be harvested per unit area. The biomass compositions presented in this paper are essential to investigate their suitability for bioenergy conversion.