Protein extraction from chlorella pyrenoidosa microalgae: Green methodologies, functional assessment, and waste stream valorization for bioenergy production.

C. pyrenoidosa, a species of microalgae, has been recognized as a viable protein source for human consumption. The primary challenges in this context are the development of an efficient extraction process and the valorization of the resultant waste streams. This study, situated within the paradigm of circular economy, presents an innovative extraction approach that achieved a protein extraction efficiency of 62 %. The extracted protein exhibited remarkable oil-water emulsifying performances, such as uniform morphology with high creaming stability, suggesting a sustainable alternative to conventional emulsifiers. Additionally, hydrothermal liquefaction technique was employed for converting the residual biomass and waste solution from the extraction process into biocrude. A biocrude yield exceeding 40 wt%, characterized by a carbon content of 73 % and a higher heating value of 36 MJ/kg, were obtained. These findings demonstrate the promising potential of microalgae biorefinery, which is significant for paving toward circular economy and zero-waste society.

Rates of Antipsychotic Drug Prescribing Among People Living With Dementia During the COVID-19 Pandemic.

Importance: Concerns have been raised that the use of antipsychotic medication for people living with dementia might have increased during the COVID-19 pandemic. Objective: To examine multinational trends in antipsychotic drug prescribing for people living with dementia before and during the COVID-19 pandemic. Design, Setting, and Participants: This multinational network cohort study used electronic health records and claims data from 8 databases in 6 countries (France, Germany, Italy, South Korea, the UK, and the US) for individuals aged 65 years or older between January 1, 2016, and November 30, 2021. Two databases each were included for South Korea and the US. Exposures: The introduction of population-wide COVID-19 restrictions from April 2020 to the latest available date of each database. Main Outcomes and Measures: The main outcomes were yearly and monthly incidence of dementia diagnosis and prevalence of people living with dementia who were prescribed antipsychotic drugs in each database. Interrupted time series analyses were used to quantify changes in prescribing rates before and after the introduction of population-wide COVID-19 restrictions. Results: A total of 857 238 people with dementia aged 65 years or older (58.0% female) were identified in 2016. Reductions in the incidence of dementia were observed in 7 databases in the early phase of the pandemic (April, May, and June 2020), with the most pronounced reduction observed in 1 of the 2 US databases (rate ratio [RR], 0.30; 95% CI, 0.27-0.32); reductions were also observed in the total number of people with dementia prescribed antipsychotic drugs in France, Italy, South Korea, the UK, and the US. Rates of antipsychotic drug prescribing for people with dementia increased in 6 databases representing all countries. Compared with the corresponding month in 2019, the most pronounced increase in 2020 was observed in May in South Korea (Kangwon National University database) (RR, 2.11; 95% CI, 1.47-3.02) and June in the UK (RR, 1.96; 95% CI, 1.24-3.09). The rates of antipsychotic drug prescribing in these 6 databases remained high in 2021. Interrupted time series analyses revealed immediate increases in the prescribing rate in Italy (RR, 1.31; 95% CI, 1.08-1.58) and in the US Medicare database (RR, 1.43; 95% CI, 1.20-1.71) after the introduction of COVID-19 restrictions. Conclusions and Relevance: This cohort study found converging evidence that the rate of antipsychotic drug prescribing to people with dementia increased in the initial months of the COVID-19 pandemic in the 6 countries studied and did not decrease to prepandemic levels after the acute phase of the pandemic had ended. These findings suggest that the pandemic disrupted the care of people living with dementia and that the development of intervention strategies is needed to ensure the quality of care.

[Fetal malnutrition assessment program].

OBJECTIVE: To study the application of ponderal index (PI), body mass index (BMI), mid-arm circumference/head circumference (MAC/HC), and Clinical Assessment of Nutritional Status (CANS) score in assessing the nutritional status of neonates at birth, and to find a simple and reliable scheme for the assessment of fetal nutritional status. METHODS: PI, BMI, MAC/HC, and CANS were used to assess the nutritional status of full-term infants and preterm infants shortly after birth. The assessment results of these methods were analyzed. RESULTS: Among the 678 full-term infants, 61, 102, 47, and 131 were diagnosed with malnutrition by PI, BMI, MAC/HC, and CANS respectively. Among the 140 preterm infants, 30, 87, 9, and 112 were diagnosed with malnutrition by PI, BMI, MAC/HC, and CANS respectively. The combination of BMI and CANS had a detection rate of 99.3% in full-term infants and 100% in preterm infants. Compared with the single method, the combination significantly improved the detection rate of malnutrition (P < 0.05), while there was no significant difference between the combination of BMI+CANS and the combination of PI+BMI+CANS (P > 0.05). CONCLUSIONS: The combination of BMI+CANS can reduce the rate of missed diagnosis of fetal malnutrition. It is therefore a simple and reliable method for the assessment of fetal malnutrition.