This study evaluates the comprehensive valorization of the byproducts derived from the two-phase olive oil elaboration process i.e., olive washing water (OWW), olive oil washing water (OOWW), and ...olive mill solid waste (OMSW) in a closed-loop process. Initially, the microalga Raphidocelis subcapitata was grown using a mixture of OWW and OOWW as the culture medium, allowing phosphate, nitrate, sugars, and soluble chemical oxygen demand removal. In a second step, the microalgal biomass grown in the mixture of washing waters was used as a co-substrate together with OMSW for an anaerobic co-digestion process. The anaerobic co-digestion of the combination of 75% OMSW–25% R. subcapitata enhanced the methane yield by 7.0 and 64.5% compared to the anaerobic digestion of the OMSW and R. subcapitata individually. This schedule of operation allowed for integration of all of the byproducts generated from the two-phase olive oil elaboration process in a full valorization system and the establishment of a circular economy concept for the olive oil industry.
The table olive industry produces a high quantity of wastewater annually. These wastewaters are very problematic because of their characteristics of high organic matter, high phenolic content, high ...salinity and conductivity. The quantities in which they are produced are also a serious problem. The worldwide production of table olives reached 2,550,000 tons in the last five campaigns, with the European Union contributing to 32% of total production. The problem of these wastewaters is focused on the Mediterranean area where the highest quantity of table olives is produced and to a lesser extent on the United States and South America. Countries like Spain produce around 540,000 tons of these wastewaters. At present, there is no standard treatment for these wastewaters with acceptable results and which is applied in the industry. Currently, the most common treatment is the storage of these wastewaters in large evaporation ponds where, during the dry season, the wastewater disappears due to evaporation. This is not a solution as the evaporation ponds depend completely on the climatology and have a high number of associated problems, such as bad odors, insect proliferation and the contamination of underground aquifers. Different studies have been carried out on table olive wastewater treatment, but the reality is that at the industrial level, none has been successfully applied. New and promising treatments are needed. The current review analyzes the situation of table olive wastewater treatment and the promising technologies for the future.
This paper presents the use of an effluent derived from two-stage
anaerobic digestion of two-phase olive mill solid waste (OMSW) as a
substrate for the production of Chlorella zofingiensis in batch ...mode.
Chlorella zofingiensis when grown autotrophycally can accumulate
significant quantities of valuable carotenoids which are used as an
additive in fish and poultry farming, as colorants in foods and in
health care products. It was found that two-phase OMSW previously
treated by two-stage anaerobic digestion and further sterilized may be
used as a culture medium for the microalgae Chlorella zofingiensis.
Typical growth curves were obtained using both the above-mentioned
anaerobic effluent and a synthetic medium. Total chemical oxygen demand
(TCOD) and soluble chemical oxygen demand (SCOD) removals of 37% and
45% respectively were achieved in batch experiments after 11 days'
operation time. The specific growth rate was lower when the treated
effluent was used as the feed substrate (0.02 h-1) in comparison to the
synthetic medium (0.03 h-1). The specific growth rates of the
exponential phases were determined by using a first-order kinetic model
applied to chlorophyll a (C a ) and total chlorophyll (TC)
concentrations, as indirect measurements of the microalgae
concentration. It was concluded that the effluent from two-stage
anaerobic digestion of two-phase OMSW constituted an appropriate
culture medium for the growth of Chlorella zofingiensis, providing a
simple technology feasible for producing a very useful product for
animal feeding.
This paper presents the use of an effluent derived from two-stage anaerobic digestion of two-phase olive mill solid waste (OMSW) as a substrate for the production of Chlorella zofingiensis in batch ...mode. Chlorella zofingiensis when grown autotrophycally can accumulate significant quantities of valuable carotenoids which are used as an additive in fish and poultry farming, as colorants in foods and in health care products. It was found that two-phase OMSW previously treated by two-stage anaerobic digestion and further sterilized may be used as a culture medium for the microalgae Chlorella zofingiensis. Typical growth curves were obtained using both the above-mentioned anaerobic effluent and a synthetic medium. Total chemical oxygen demand (TCOD) and soluble chemical oxygen demand (SCOD) removals of 37% and 45% respectively were achieved in batch experiments after 11 days’ operation time. The specific growth rate was lower when the treated effluent was used as the feed substrate (0.02 h-1) in comparison to the synthetic medium (0.03 h-1). The specific growth rates of the exponential phases were determined by using a first-order kinetic model applied to chlorophyll a (Ca) and total chlorophyll (TC) concentrations, as indirect measurements of the microalgae concentration. It was concluded that the effluent from two-stage anaerobic digestion of two-phase OMSW constituted an appropriate culture medium for the growth of Chlorella zofingiensis, providing a simple technology feasible for producing a very useful product for animal feeding.
COVID-19 is responsible for high mortality, but robust machine learning-based predictors of mortality are lacking. To generate a model for predicting mortality in patients hospitalized with COVID-19 ...using Gradient Boosting Decision Trees (GBDT). The Spanish SEMI-COVID-19 registry includes 24,514 pseudo-anonymized cases of patients hospitalized with COVID-19 from 1 February 2020 to 5 December 2021. This registry was used as a GBDT machine learning model, employing the CatBoost and BorutaShap classifier to select the most relevant indicators and generate a mortality prediction model by risk level, ranging from 0 to 1. The model was validated by separating patients according to admission date, using the period 1 February to 31 December 2020 (first and second waves, pre-vaccination period) for training, and 1 January to 30 November 2021 (vaccination period) for the test group. An ensemble of ten models with different random seeds was constructed, separating 80% of the patients for training and 20% from the end of the training period for cross-validation. The area under the receiver operating characteristics curve (AUC) was used as a performance metric. Clinical and laboratory data from 23,983 patients were analyzed. CatBoost mortality prediction models achieved an AUC performance of 84.76 (standard deviation 0.45) for patients in the test group (potentially vaccinated patients not included in model training) using 16 features. The performance of the 16-parameter GBDT model for predicting COVID-19 hospital mortality, although requiring a relatively large number of predictors, shows a high predictive capacity.
Background: Pseudomonas aeruginosa healthcare-associated infections are one of the top antimicrobial resistance threats world-wide. In order to analyze the current trends, we performed a Spanish ...nation-wide high-resolution analysis of the susceptibility profiles, the genomic epidemiology and the resistome of P. aeruginosa over a five-year time lapse. Methods: A total of 3.180 nonduplicated P. aeruginosa clinical isolates from two Spanish nation-wide surveys performed in October 2017 and 2022 were analyzed. MICs of 13 antipseudomonals were determined by ISO-EUCAST. Multidrug resistance (MDR)/extensively drug resistance (XDR)/difficult to treat resistance (DTR)/pandrug resistance (PDR) profiles were defined following established criteria. All XDR/DTR isolates were subjected to whole genome sequencing (WGS). Findings: A decrease in resistance to all tested antibiotics, including older and newer antimicrobials, was observed in 2022 vs 2017. Likewise, a major reduction of XDR (15.2% vs 5.9%) and DTR (4.2 vs 2.1%) profiles was evidenced, and even more patent among ICU isolates XDR (26.0% vs 6.0%) and DTR (8.9% vs 2.6%) (p < 0.001). The prevalence of Extended-spectrum β-lactamase/carbapenemase production was slightly lower in 2022 (2.1%. vs 3.1%, p = 0.064). However, there was a significant increase in the proportion of carbapenemase production among carbapenem-resistant strains (29.4% vs 18.1%, p = 0.0246). While ST175 was still the most frequent clone among XDR, a slight reduction in its prevalence was noted (35.9% vs 45.5%, p = 0.106) as opposed to ST235 which increased significantly (24.3% vs 12.3%, p = 0.0062). Interpretation: While the generalized decrease in P. aeruginosa resistance, linked to a major reduction in the prevalence of XDR strains, is encouraging, the negative counterpart is the increase in the proportion of XDR strains producing carbapenemases, associated to the significant advance of the concerning world-wide disseminated hypervirulent high-risk clone ST235. Continued high-resolution surveillance, integrating phenotypic and genomic data, is necessary for understanding resistance trends and analyzing the impact of national plans on antimicrobial resistance. Funding: MSD and the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea—NextGenerationEU.
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