Utilization of centrate from wastewater treatment for the outdoor production of Nannochloropsis gaditana biomass at pilot-scale

In this work, the outdoor pilot-scale production of marine microalga Nannochloropsis gaditana using centrate from the anaerobic digestion of municipal wastewater was evaluated. For this, outdoor continuous cultures were performed in both tubular and raceways reactors mixing seawater with different centrate percentages (15%, 20% and 30%) as culture medium. It was demonstrated that N. gaditana can be produced using centrate as the only nutrients source but at percentages below 30%. At this level inhibition was caused by an excess of ammonium in both photobioreactors, as confirmed by chlorophyll fluorescence and average irradiance data, thus reducing productivity. At 15% and 20% centrate percentages, biomass productivity was equal to that measured when using Algal culture medium, of 0.48 and 0.10 g·l-1·day-1 for tubular and raceway reactors respectively. During the experiments nitrogen depuration decreased from 85% to 63% in tubular reactors with the increase of centrate percentage in culture medium and the decrease in biomass productivity, while in raceway reactors an opposite behavior was observed due to ammonia stripping from the cultures. Phosphorus depuration from the culture medium was 85% whatever the system used and the centrate percentage in culture medium indicating a phosphorus limitation into the cultures. By supplying additional phosphorus, to achieve an N:P ratio of 5, it was possible to enhance productivity and increase nitrogen depuration in both systems. The use of centrate is confirmed as a useful method for reducing microalgae production costs and for increasing process sustainability. Consequently, it is demonstrated that for the production of microalgae biomass, centrate from wastewater treatment plants can be used as the exclusive nutrient source, achieving high productivities and nutrient removal rates if using suitable strains and if the system is operated adequately

A Reaction-Diffusion Numerical Model to Predict Cardiac Tissues Regeneration Via Stem Cell Therapy

Myocardial infarction is a leading cause of morbidity and mortality in the industrialized world. Extensive loss of cardiomyocytes, substituted by scarred tissue, is the key pathological mechanism leading to post infarc- tion heart failure [1]. The use of exogenous cells to replace lost cardiomy- ocytes has been demonstrated in animal models and in clinical trials by transplanting mesenchymal stem cells (MSCs) into the infarcted area. To optimize the initial conditions of the stem cell therapy, many experimen- tal studies are focused on determining the number and the localization of stem cells that must be implanted near the necrotic area. In this work we develop a quantitative numerical model able to simulate substrate con- centration profile, stem cells distribution and their proliferation near the ischemic area. The model describes the cell growth, the nutrient transport and its consumption through reaction-diffusion equations. The shrinking of the necrotic area leads in fact to a moving boundary problem. Some preliminary results, obtained in a 3D framework, are shown and discuss

Learning models for classifying Raman spectra of genomic DNA from tumor subtypes

An early and accurate detection of different subtypes of tumors is crucial for an effective guidance to personalized therapy and in predicting the ability of tumor to metastasize. Here we exploit the Surface Enhanced Raman Scattering (SERS) platform, based on disordered silver coated silicon nanowires (Ag/SiNWs), to efficiently discriminate genomic DNA of different subtypes of melanoma and colon tumors. The diagnostic information is obtained by performing label free Raman maps of the dried drops of DNA solutions onto the Ag/NWs mat and leveraging the classification ability of learning models to reveal the specific and distinct physico-chemical interaction of tumor DNA molecules with the Ag/NW, here supposed to be partly caused by a different DNA methylation degree

Learning models for classifying Raman spectra of genomic DNA from tumor subtypes

An early detection of different tumor subtypes is crucial for an effective guidance to personalized therapy. While much efforts focus on decoding the sequence of DNA basis to detect the genetic mutations related to cancer, it is becoming clear that physical properties, including structural conformation, stiffness, and shape, as well as biological processes, such as methylation, can be pivotal to recognize DNA modifications. Here we exploit the Surface Enhanced Raman Scattering (SERS) platform, based on disordered silver coated--silicon nanowires, to investigate genomic DNA from subtypes of melanoma and colon cancers and to efficiently discriminate tumor and healthy cells, as well as the different tumor subtypes. The diagnostic information is obtained by performing label--free Raman maps of the dried drops of DNA solutions onto the Ag/NWs mat, and leveraging the classification ability of learning models to reveal the specific and distinct interaction of healthy and tumor DNA molecules with nanowires

Heparan sulfate proteoglycan syndecan-3 is a novel receptor for GDNF, neurturin, and artemin

Syndecan-3 may act alone or as a coreceptor with RET to promote cell spreading, neurite outgrowth, and migration of cortical neurons by GNDF, NRTN, and ARTN

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

A simplified process of swine slurry treatment by primary filtration and Haematococcus pluvialis culture to produce low cost astaxanthin

A simplified process for treating swine slurry through primary filtration and subsequent depuration of thefiltrate with the astaxanthin-rich microalga Haematococcus pluvialis is proposed. The first step comprisesa low-cost filtration system capable of reducing 66% of ammonia, 7% of phosphorus and 19% of chemicaloxygen demand, and increasing the concentration of nitrate, being this useful for subsequent growthof the algae. The second step comprises the discontinuous cultivation of H. pluvialis in diluted filteredslurry. The optimal dilution was researched by testing undiluted and 2, 4 and 8-fold diluted filtrate. Thisstep led to a drastic reduction in macro and micronutrients concentration (up to 99% for NO3-N andNH4-N, 98% for TP and 26% for chemical oxygen demand). After H. pluvialis growth the accumulation ofastaxanthin took place for 14 d in nutrient-deprived conditions: an astaxanthin accumulation of 1.27%on a dry weight basis was measured. These results indicate the possibility to couple low-cost filtrationand microalgae production to recover nutrients from swine wastewaters and to add value by producingvaluable astaxanthin for the feed market or for an on-farm utilization as feed addictive