An Integrated Process Analysis for Producing Glycerol Carbonate from CO2 and Glycerol.

Glycerol carbonate (GC) is one of the most attractive green chemicals involved in several applications such as polymer synthesis, e. g., the production of polyurethanes and polycarbonates. This relevant chemical can be produced, in a green way, using CO2 (from carbon capture) and glycerol (a byproduct from biodiesel manufacturing). Therefore, in this work, a comprehensive analysis of the GC production process is conducted based on the following synthesis route: urea-dimethyl carbonate-GC using carbon dioxide and glycerol as the main raw materials where the synthesis pathway was efficiently integrated using Aspen Plus. A techno-economic analysis was performed in order to estimate the required capital investment and operating cost for the whole GC process, providing insights on individual capital cost requirements for the urea, dimethyl carbonate, and GC production sections. A total capital cost of $192.1 MM, and a total operating cost of $225.7 MM/y were estimated for the process. The total annualized cost was estimated as $1,558 USD/t of GC produced, competitive with current market price.

Solar photovoltaic panel production in Mexico: A novel machine learning approach.

This study examines the potential for widespread solar photovoltaic panel production in Mexico and emphasizes the country's unique qualities that position it as a strong manufacturing candidate in this field. An advanced model based on artificial neural networks has been developed to predict solar photovoltaic panel plant metrics. This model integrates a state-of-the-art non-linear programming framework using Pyomo as well as an innovative optimization and machine learning toolkit library. This approach creates surrogate models for individual photovoltaic plants including production timelines. While this research, conducted through extensive simulations and meticulous computations, unveiled that Latin America has been significantly underrepresented in the production of silicon, wafers, cells, and modules within the global market; it also demonstrates the substantial potential of scaling up photovoltaic panel production in Mexico, leading to significant economic, social, and environmental benefits. By hyperparameter optimization, an outstanding and competitive artificial neural network model has been developed with a coefficient of determination values above 0.99 for all output variables. It has been found that water and energy consumption during PV panel production is remarkable. However, water consumption (33.16 × 10-4 m3/kWh) and the emissions generated (1.12 × 10-6 TonCO2/kWh) during energy production are significantly lower than those of conventional power plants. Notably, the results highlight a positive economic trend, with module production plants generating the highest profits (35.7%) among all production stages, while polycrystalline silicon production plants yield comparatively lower earnings (13.0%). Furthermore, this study underscores a critical factor in the photovoltaic panel production process which is that cell production plants contribute the most to energy consumption (39.7%) due to their intricate multi-stage processes. The blending of Machine Learning and optimization models heralds a new era in resource allocation for a more sustainable renewable energy sector, offering a brighter, greener future.

A systematic approach for assessing water, energy and food security during the COVID-19 pandemic: case study of Mexico.

Assessing the security of the water-energy-food nexus is a topic of great importance, which allows determining the situation of each resource to implement actions for sustainable management of these resources in today's society. For this reason, a systematic procedure is proposed to evaluate the synergies of the water-energy-food nexus in a large region that is divided into subregions that allow considering their interactions. The new procedure considers the availability, accessibility and regional interdependence of resources while annexing economic and social aspects. A composite index called the WEF Global Index is developed, which involves the WEF nexus index and has nine indicators that evaluate the availability, accessibility and regional interdependence of each resource in the water-energy-food nexus. This new index considers the Gross Domestic Product per capita and the involved population. As a case study, the 32 states of Mexico were considered to assess the effects of the COVID-19 pandemic on the economy and the security of the water-energy-food nexus at the state level. For this, the composite index was evaluated in the years 2019 and 2020. The results show that from 2019 to 2020, the value of the global index increased in 13 states, in 21 states the security index of the WEF nexus increased, and in 9 states the GDP per capita index increased. On the other hand, the results indicate that in 11 states there was no improvement in the nexus security index due to the increase in water demand, which considerably affected the water availability indicator. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-022-02671-2.

High-pressure technology for Sargassum spp biomass pretreatment and fractionation in the third generation of bioethanol production.

Sargassum spp is an invasive macroalgae and an alternative feedstock for bioethanol production. Sargassum spp biomass was subjected to high-pressure technology for biomass fractionation under different operating conditions of temperature and residence time to obtain glucan enriched pretreated solids (32.22 g/100 g of raw material). Enzyme hydrolysis process at high pretreated solid loading (13%, w/v) and enzyme loading of 10 FPU/g of glucan was performed, obtaining 43.01 g/L of glucose corresponding to a conversion yield of 92.12%. Finally, a pre-simultaneous saccharification and fermentation strategy (PSSF) was performed to produce bioethanol. This operational strategy produced 45.66 g/L of glucose in the pre-saccharification stage, and 18.14 g/L of bioethanol was produced with a glucose to bioethanol conversion yield of 76.23%. The development of this process highlights the feasibility of bioethanol production from macroalgal biomass in the biorefinery concept.

Association of P10L Polymorphism in Melanopsin Gene with Chronic Insomnia in Mexicans.

The aim of this pilot study was to determine the association of the P10L (rs2675703) polymorphism of the OPN4 gene with chronic insomnia in uncertain etiology in a Mexican population. A case control study was performed including 98 healthy subjects and 29 individuals with chronic insomnia not related to mental disorders, medical condition, medication or substance abuse. Samples were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Genetic analyses showed that the T allele of P10L increased risk to chronic insomnia in a dominant model (p = 1 ×10-4; odds ratio (OR) = 9.37, CI = 8.18-335.66, Kelsey statistical power (KSP) = 99.9%), and in a recessive model (p = 7.5 × 10-5, OR = 9.37, KSP = 99.3%, CI = 2.7-34.29). In the insomnia group, we did not find a correlation between genotypes and chronotype (p = 0.219 Fisher's exact test), severity of chronic insomnia using ISI score (p = 0.082 Fisher's exact test) and ESS score (p ˃ 0.999 Fisher's exact test). However, evening chronotype was correlated to daytime sleepiness severity, individuals with an eveningness chronotype had more severe drowsiness according to their insomnia severity index (ISI) score (p = 0.021 Fisher's exact test) and Epworth sleepiness scale (ESS) score (p = 0.015 Fisher's exact test) than the morningness and intermediate chronotype. We demonstrated that the T allele of the P10L polymorphism in the OPN4 gene is associated with chronic insomnia in Mexicans. We suggest the need to conduct larger studies in different ethnic populations to test the probable association and function of P10L and other SNPs in the OPN4 gene and in the onset of chronic insomnia.

Biological Properties of a Novel Multifunctional Host Defense Peptide from the Skin Secretion of the Chaco Tree Frog, Boana raniceps.

In recent years, the number of new antimicrobial drugs launched on the market has decreased considerably even though there has been an increase in the number of resistant microbial strains. Thus, antimicrobial resistance has become a serious public health problem. Amphibian skin secretions are a rich source of host defense peptides, which generally are cationic and hydrophobic molecules, with a broad-spectrum of activity. In this study, one novel multifunctional defense peptide was isolated from the skin secretion of the Chaco tree frog, Boana raniceps. Figainin 2 (1FLGAILKIGHALAKTVLPMVTNAFKPKQ28) is cationic and hydrophobic, adopts an α-helical structure in 50% (v/v) trifluoroethanol (TFE), and is thermally stable. This peptide exhibited activity against Gram-negative and Gram-positive pathogenic bacteria arboviruses, T. cruzi epimastigotes; however, it did not show activity against yeasts. Figainin 2 also showed antiproliferative activity on cancer cells, is moderately active on human erythrocytes, and activates the oxidative burst in human neutrophils.

Cytotoxic Activity and Antiproliferative Effects of Crude Skin Secretion from Physalaemus nattereri (Anura: Leptodactylidae) on in vitro Melanoma Cells.

Anuran secretions are rich sources of bioactive molecules, including antimicrobial and antitumoral compounds. The aims of this study were to investigate the therapeutic potential of Physalaemus nattereri skin secretion against skin cancer cells, and to assess its cytotoxic action mechanisms on the murine melanoma cell line B16F10. Our results demonstrated that the crude secretion reduced the viability of B16F10 cells, causing changes in cell morphology (e.g., round shape and structure shrinkage), reduction in mitochondrial membrane potential, increase in phosphatidylserine exposure, and cell cycle arrest in S-phase. Together, these changes suggest that tumor cells die by apoptosis. This skin secretion was also subjected to chromatographic fractioning using RP-HPLC, and eluted fractions were assayed for antiproliferative and antibacterial activities. Three active fractions showed molecular mass components in a range compatible with peptides. Although the specific mechanisms causing the reduced cell viability and cytotoxicity after the treatment with crude secretion are still unknown, it may be considered that molecules, such as the peptides found in the secretion, are effective against B16F10 tumor cells. Considering the growing need for new anticancer drugs, data presented in this study strongly reinforce the validity of P. nattereri crude secretion as a rich source of new anticancer molecules.