An empirical analysis of the relationship among price, demand and CO2 emissions in the Spanish electricity market.

CO2 emissions play a crucial role in international politics. Countries enter into agreements to reduce the amount of pollution emitted into the atmosphere. Energy generation is one of the main contributors to pollution and is generally considered the main cause of climate change. Despite the interest in reducing CO2 emissions, few studies have focused on investigating energy pricing technologies. This article analyzes the technologies used to meet the demand for electricity from 2016 to 2021. The analysis is based on data provided by the Spanish Electricity System regulator, using statistical and clustering techniques. The objective is to establish the relationship between the level of pollution of electricity generation technologies and the hourly price and demand. Overall, the results suggest that there are two distinct periods with respect to the technologies used in the studied years, with a trend toward the use of cleaner technologies and a decrease in power generation using fossil fuels. It is also surprising that in the years 2016 to 2018, the most polluting technologies offered the cheapest prices.

Development of a liver graft assessment expert machine-learning system: when the artificial intelligence helps liver transplant surgeons.

Background: The complex process of liver graft assessment is one point for improvement in liver transplantation. The main objective of this study is to develop a tool that supports the surgeon who is responsible for liver donation in the decision-making process whether to accept a graft or not using the initial variables available to it. Material and method: Liver graft samples candidate for liver transplantation after donor brain death were studied. All of them were evaluated "in situ" for transplantation, and those discarded after the "in situ" evaluation were considered as no transplantable liver grafts, while those grafts transplanted after "in situ" evaluation were considered as transplantable liver grafts. First, a single-center, retrospective and cohort study identifying the risk factors associated with the no transplantable group was performed. Then, a prediction model decision support system based on machine learning, and using a tree ensemble boosting classifier that is capable of helping to decide whether to accept or decline a donor liver graft, was developed. Results: A total of 350 liver grafts that were evaluated for liver transplantation were studied. Steatosis was the most frequent reason for classifying grafts as no transplantable, and the main risk factors identified in the univariant study were age, dyslipidemia, personal medical history, personal surgical history, bilirubinemia, and the result of previous liver ultrasound (p < 0.05). When studying the developed model, we observe that the best performance reordering in terms of accuracy corresponds to 76.29% with an area under the curve of 0.79. Furthermore, the model provides a classification together with a confidence index of reliability, for most cases in our data, with the probability of success in the prediction being above 0.85. Conclusion: The tool presented in this study obtains a high accuracy in predicting whether a liver graft will be transplanted or deemed non-transplantable based on the initial variables assigned to it. The inherent capacity for improvement in the system causes the rate of correct predictions to increase as new data are entered. Therefore, we believe it is a tool that can help optimize the graft pool for liver transplantation.

Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients.

Background and purpose: Radiation-induced toxicities are common adverse events in lung cancer (LC) patients undergoing radiotherapy (RT). An accurate prediction of these adverse events might facilitate an informed and shared decision-making process between patient and radiation oncologist with a clearer view of life-balance implications in treatment choices. This work provides a benchmark of machine learning (ML) approaches to predict radiation-induced toxicities in LC patients built upon a real-world health dataset based on a generalizable methodology for their implementation and external validation. Materials and Methods: Ten feature selection (FS) methods were combined with five ML-based classifiers to predict six RT-induced toxicities (acute esophagitis, acute cough, acute dyspnea, acute pneumonitis, chronic dyspnea, and chronic pneumonitis). A real-world health dataset (RWHD) built from 875 consecutive LC patients was used to train and validate the resulting 300 predictive models. Internal and external accuracy was calculated in terms of AUC per clinical endpoint, FS method, and ML-based classifier under analysis. Results: Best performing predictive models obtained per clinical endpoint achieved comparable performances to methods from state-of-the-art at internal validation (AUC ≥ 0.81 in all cases) and at external validation (AUC ≥ 0.73 in 5 out of 6 cases). Conclusion: A benchmark of 300 different ML-based approaches has been tested against a RWHD achieving satisfactory results following a generalizable methodology. The outcomes suggest potential relationships between underrecognized clinical factors and the onset of acute esophagitis or chronic dyspnea, thus demonstrating the potential that ML-based approaches have to generate novel data-driven hypotheses in the field.

Movement Velocity as an Indicator of Mechanical Fatigue and Resistance Exercise Intensity in Cross Modalities.

Purpose: This study analyzed the acute mechanical response to three workouts of the day (WOD) protocols in as many repetitions as possible (AMRAP), every minute on the minute (EMOM), and for time (FT) models by quantifying the degree of mechanical fatigue induced by popular resistance exercises in the Cross modalities, front squat (FS), and shoulder press (SP). We also analyzed whether the exercises' fastest velocity (Vfastest) could be an objective indicator of relative intensity (%1RM). Methods: Nine trained men performed three FS and SP exercises protocols. The degree of fatigue was quantified by the velocity loss (VL) achieved in both exercises and the velocity loss achieved in the WOD (VLWOD). Results: The VLWOD in the AMRAP, EMOM, and FT protocols was 73.2 ± 10.9%, 61.6 ± 15.1%, and 76.1 ± 8.8%, respectively. In the AMRAP and FT protocol, the Vfastest showed very strong relationships with the %1RM for FS and SP (r = -0.83, -0.75, respectively, p < .01); while in the EMOM protocol, there was a strong relationship between these variables, only for the SP (r = -0.61, p < .05). In the FT protocol, we observed an extremely strong relationship for FS (r = -0.91, p < .001) and very strong (r = -0.71, p < .05) for SP between these variables. Conclusion: Therefore, the AMRAP and FT training models induce the highest degrees of mechanical fatigue in the FS and SP exercises, and the Vfastest is a reliable tool for estimating relative intensity in resistance exercises of Cross modalities.

Sustainable Feedstocks and Challenges in Biodiesel Production: An Advanced Bibliometric Analysis.

Biodiesel can be produced from vegetable oils, animal fats, frying oils, and from microorganism-synthesized oils. These sources render biodiesel an easily biodegradable fuel. The aim of this work was to perform an advanced bibliometric analysis of primary studies relating to biodiesel production worldwide by identifying the key countries and regions that have shown a strong engagement in this area, and by understanding the dynamics of their collaboration and research outputs. Additionally, an assessment of the main primary feedstocks employed in this research was carried out, along with an analysis of the current and future trends that are expected to define new paths and methodologies to be used in the manufacture of biodegradable and renewable fuels. A total of 4586 academic outputs were selected, including peer-reviewed research articles, conference papers, and literature reviews related to biodiesel production, in the time period spanning from 2010 to 2021. Articles that focused on feedstocks for the production of biodiesel were also included, with a search that returned 330 papers. Lastly, 60 articles relating to biodiesel production via sewage were specifically included to allow for an analysis of this source as a promising feedstock in the future of the biofuel market. Via the geocoding and the document analyses performed, we concluded that China, Malaysia, and India are the largest writers of articles in this area, revealing a great interest in biofuels in Asia. Additionally, it was noted that environmental concerns have caused authors to conduct research on feedstocks that can address the sustainability challenges in the production of biodiesel.

The Chemistry and Applications of Metal-Organic Frameworks (MOFs) as Industrial Enzyme Immobilization Systems.

Enzymatic biocatalysis is a sustainable technology. Enzymes are versatile and highly efficient biocatalysts, and have been widely employed due to their biodegradable nature. However, because the three-dimensional structure of these enzymes is predominantly maintained by weaker non-covalent interactions, external conditions, such as temperature and pH variations, as well as the presence of chemical compounds, can modify or even neutralize their biological activity. The enablement of this category of processes is the result of the several advances in the areas of molecular biology and biotechnology achieved over the past two decades. In this scenario, metal-organic frameworks (MOFs) are highlighted as efficient supports for enzyme immobilization. They can be used to 'house' a specific enzyme, providing it with protection from environmental influences. This review discusses MOFs as structures; emphasizes their synthesis strategies, properties, and applications; explores the existing methods of using immobilization processes of various enzymes; and lists their possible chemical modifications and combinations with other compounds to formulate the ideal supports for a given application.

Chemical and physical Chitosan modification for designing enzymatic industrial biocatalysts: How to choose the best strategy?

Chitosan is one of the most abundant natural polymer worldwide, and due to its inherent characteristics, its use in industrial processes has been extensively explored. Because it is biodegradable, biocompatible, non-toxic, hydrophilic, cheap, and has good physical-chemical stability, it is seen as an excellent alternative for the replacement of synthetic materials in the search for more sustainable production methodologies. Thus being, a possible biotechnological application of Chitosan is as a direct support for enzyme immobilization. However, its applicability is quite specific, and to overcome this issue, alternative pretreatments are required, such as chemical and physical modifications to its structure, enabling its use in a wider array of applications. This review aims to present the topic in detail, by exploring and discussing methods of employment of Chitosan in enzymatic immobilization processes with various enzymes, presenting its advantages and disadvantages, as well as listing possible chemical modifications and combinations with other compounds for formulating an ideal support for this purpose. First, we will present Chitosan emphasizing its characteristics that allow its use as enzyme support. Furthermore, we will discuss possible physicochemical modifications that can be made to Chitosan, mentioning the improvements obtained in each process. These discussions will enable a comprehensive comparison between, and an informed choice of, the best technologies concerning enzyme immobilization and the application conditions of the biocatalyst.

Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance.

Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the 5-year survival rate of breast cancer is relatively high, recurrence is also common which often involves metastasis with its consequent threat for patients. DNA methylation-derived databases have become an interesting primary source for supervised knowledge extraction regarding breast cancer. Unfortunately, the study of DNA methylation involves the processing of hundreds of thousands of features for every patient. DNA methylation is featured by High Dimension Low Sample Size which has shown well-known issues regarding feature selection and generation. Autoencoders (AEs) appear as a specific technique for conducting nonlinear feature fusion. Our main objective in this work is to design a procedure to summarize DNA methylation by taking advantage of AEs. Our proposal is able to generate new features from the values of CpG sites of patients with and without recurrence. Then, a limited set of relevant genes to characterize breast cancer recurrence is proposed by the application of survival analysis and a pondered ranking of genes according to the distribution of their CpG sites. To test our proposal we have selected a dataset from The Cancer Genome Atlas data portal and an AE with a single-hidden layer. The literature and enrichment analysis (based on genomic context and functional annotation) conducted regarding the genes obtained with our experiment confirmed that all of these genes were related to breast cancer recurrence.

Different types of functional training on the functionality and quality of life in postmenopausal women: a randomized and controlled trial.

BACKGROUND: Physical exercise is widely recommended for improving physical fitness. However, the most effective training method in improving the daily life of postmenopausal women is not clear. Therefore, this study compares different ways of functional training, focused on the task, and directed to the physical abilities on the functionality and quality of life of the postmenopausal women. METHODS: Forty-seven participants were randomly assigned into three groups: element-based functional training (EBFT); task-specific-based functional training (TSBFT); and the control group (CG). The intervention lasted fourteen weeks, with three weekly sessions stimulating several physical valences in the same session. The global functionality, functional reach, gait speed, handgrip strength, jumping ability, and quality of life before and after the intervention were evaluated. RESULTS: A similar increase was detected in both experimental groups for the variables-analyzed when compared to the initial moment (P<0.05), except in the dynamic postural control (P>0.05), which showed no difference. However, in the tests of rising from the floor and handgrip strength, only the task-specific-based functional training showed difference over time (P<0.05). CONCLUSIONS: Functional training protocols improve the performance in daily activities of postmenopausal women. However, task-specific-based functional training is more effective when compared to the control group in the analyzed variables.

Lipase From Rhizomucor miehei Immobilized on Magnetic Nanoparticles: Performance in Fatty Acid Ethyl Ester (FAEE) Optimized Production by the Taguchi Method.

In this communication, it was evaluated the production of fatty acid ethyl ester (FAAE) from the free fatty acids of babassu oil catalyzed by lipase from Rhizomucor miehei (RML) immobilized on magnetic nanoparticles (MNP) coated with 3-aminopropyltriethoxysilane (APTES), Fe3O4@APTES-RML or RML-MNP for short. MNPs were prepared by co-precipitation coated with 3-aminopropyltriethoxysilane and used as a support to immobilize RML (immobilization yield: 94.7 ± 1.0%; biocatalyst activity: 341.3 ± 1.2 U p -NPB/g), which were also activated with glutaraldehyde and then used to immobilize RML (immobilization yield: 91.9 ± 0.2%; biocatalyst activity: 199.6 ± 3.5 U p -NPB/g). RML-MNP was characterized by X-Ray Powder Diffraction (XRPD), Fourier Transform-Infrared (FTIR) spectroscopy and Scanning Electron Microscope (SEM), proving the incorporation and immobilization of RML on the APTES matrix. In addition, the immobilized biocatalyst presented at 60°C a half-life 16-19 times greater than that of the soluble lipase in the pH range 5-10. RML and RML-MNP showed higher activity at pH 7; the immobilized enzyme was more active than the free enzyme in the pH range (5-10) analyzed. For the production of fatty acid ethyl ester, under optimal conditions [40°C, 6 h, 1:1 (FFAs/alcohol)] determined by the Taguchi method, it was possible to obtain conversion of 81.7 ± 0.7% using 5% of RML-MNP.

Modulation of lipase B from Candida antarctica properties via covalent immobilization on eco-friendly support for enzymatic kinetic resolution of rac-indanyl acetate.

In this study, the modulation of enzymatic biocatalysts were developed by the use of lipase B from Candida antarctica covalently immobilized on an eco-friendly support, cashew apple bagasse, activated with 10% glycidol-ethylenediamine-glutaraldehyde (GEG) under different immobilization strategies (5 mM or 100 mM ionic strength and in absence or presence of 0.5% (v/v) Triton X-100). The biocatalysts were characterized for thermal and organic solvents stabilities and compared with the soluble enzyme. The biocatalysts were then applied to the hydrolysis of the rac-indanyl acetate (2:1 ratio enzyme/substrate) at pH 7.0 and 30 °C for 24 h. For all the strategies evaluated, GEG promoted kinetic resolution of rac-indanyl acetate with maximum conversion (50%) and led to (R)-indanol with excellent enantiomeric excess (97%), maintaining the maximum conversion for five consecutive cycles of hydrolysis. Therefore, the use of cashew apple bagasse has proved to be a promising eco-friendly support for enzyme immobilization, since it resulted in stable biocatalysts for enzymatic kinetic resolution.

A new heterofunctional support for enzyme immobilization: PEI functionalized Fe3O4 MNPs activated with divinyl sulfone. Application in the immobilization of lipase from Thermomyces lanuginosus.

Lipase from Thermomyces lanuginosus (TLL) was immobilized onto a novel heterofunctional support, divinyl sulfone (DVS) superparamagnetic nanoparticles (SPMNs) functionalized with polyethyleneimine (PEI). Particle size and zeta potential measurements, elemental analysis, X-ray powder diffraction, magnetic measurements, and infrared spectroscopy analysis were used to characterize the TLL preparations. At pH 10, it was possible to achieve 100 % of immobilization yield in 1 h. The immobilization pH gives TLL preparations with different stabilities; indeed the TLL preparation immobilized at pH 5.0 was the most stable during the thermal inactivation at all pH values. For the hydrolysis of racemic methyl mandelate, the nanobiocatalysts immobilized at pH 5.0 and blocked with ethylenediamine (EDA) and ethanolamine (ETA) obtained good enantioselectivities (68 % and 72 %, respectively) with high catalytic activities in the reaction medium at pH 7.0. The operational stability of the systems was evaluated in the esterification reaction of benzyl alcohol, obtaining up to 61 % conversion after the seventh reaction cycle. These results show that SPMN@PEI-DVS support is a robust strategy for the easy and rapid recovery of the nanobiocatalyst by applying a magnetic field, showing great potential for industrial applications.

Sonohydrolysis using an enzymatic cocktail in the preparation of free fatty acid.

In this work, the concept of lipase cocktail has been proposed in the ultrasound-assisted hydrolysis of coconut oil. Lipase from Thermomyces lanuginosus (TLL), lipase from Rhizomucor miehei (RML), and lipase B from Candida antarctica (CALB) were evaluated as biocatalysts in different combinations. The best conversion (33.66%) was achieved using only RML; however, the best lipase cocktail (75% RML and 25% CALB) proposed by the triangular response surface was used to achieve higher conversions. At the best lipase cocktail, reaction parameters [temperature, biocatalyst content and molar ratio (water/oil)] were optimized by a Central Composite Design, allowing to obtain more than 98% of conversion in the hydrolysis of coconut oil in 3 h of incubation at 37 kHz, 300 W and 45 °C by using 20% of the lipase cocktail (w/w) and a molar ratio of 7.5:1 (water/oil). The lipase cocktail retained about 50% of its initial activity after three consecutive cycles of hydrolysis. To the authors' knowledge, up to date, this communication is the first report in the literature for the ultrasound-assisted hydrolysis of coconut oil catalyzed by a cocktail of lipases. Under ultrasound irradiation, the concept of lipase cocktail was successfully applied, and this strategy could be useful for the other types of reactions using heterogeneous substrates.

Live and frozen Artemia nauplii for catfish Lophiosilurus alexandri (Steindachner, 1876) larvae in different salinities.

The objective of the study was to verify the combination of live and frozen Artemia nauplii, in different salinized water, and its influence in growth and survival of the catfish Lophiosilurus alexandri (Steindachner, 1876) larvae. Larvae were exposed to a combination of two feeds and two different salinities: live Artemia nauplii + 0‰ salinity in the water; live Artemia nauplii + 2‰ salinity in the water; frozen Artemia nauplii + 0‰ salinity in the water; and frozen Artemia nauplii + 2‰ salinity in the water. The experiment was conducted in a randomized design, in a 2 × 2 factorial scheme, 5 replicates, during 15 days. The larvae final weight, weight gain, food conversion, standard and total length, biomass, survival, body width, intestinal quotient, Fulton's condition factor, and water quality were evaluated. The use of Artemia nauplii and 2 ppm salinized water for L. alexandri larviculture proved to be adequate providing greater growth. This was due to Artemia nauplii being kept alive and attractive for the cultivation of larvae in salinized water, even though salt was a stress factor. Already, the frozen Artemia nauplii was a viable food but should be used preferably in times of lack of live nauplii and without salinization of the water.

Comparative larval ontogeny of two fish species (Characiformes and Siluriformes) endemic to the São Francisco River in Brazil.

The aim of the present study was to perform comparative histological analyses of the ontogenetic development of two fish species endemic to the São Francisco River in Brazil: Prochilodus argenteus and Lophiosilurus alexandri. Histological analyses were performed every 24 h from the moment of hatching until 14 days post-hatching (dph) for the observation of larval development and until 39 dph for the observation of gonadal development. Whole larvae were fixed in Bouin's solution and the histological slides were stained with haematoxylin-eosin. Lophiosilurus alexandri larvae had a larger body size compared with P. argenteus larvae since hatching. Lophiosilurus alexandri larvae had mouth opening and pigmentation of the eyes upon hatching, whereas these events were observed at 1 dph in P. argenteus larvae. The visualisation and the inflation of the swim bladder occurred at 1 and 3 dph, respectively, in the P. argenteus, whereas these events occurred at 2 and 8 dph, respectively, in L. alexandri. Yolk granules were absorbed at 4 dph in P. argenteus and the 10 dph in L. alexandri. At 7 dph, the digestive tube was more differentiated in L. alexandri than P. argenteus and at 14 dph, the digestive system of both species had features of their eating habits: broad stomach and short intestine in L. alexandri, typical of carnivorous habits; stomach with a mechanical function and long intestine in P. argenteus, typical of detritivorous habits. The epithelial lining tissue, formed by a single layer of cells in the newly hatched larvae (0 dph), differentiated throughout the study, exhibiting scales in P. argenteus and numerous club cells in the middle epithelial region of L. alexandri at 39 dph. Undifferentiated gonads with somatic cells and primordial germ cells were observed at 39 dph, with caudal-cranial migration since 1 dph in both species. The anatomic changes during the ontogeny of P. argenteus and L. alexandri larvae are directly associated with the evolutionary history of each species, which explains their feeding habits, behaviour and distribution in the environment: Prochilodus argenteus is detritivorous and actively swims in the water column, whereas L. alexandri is carnivorous and inhabits bottom regions. At 39 dph neither species exhibited sexual differentiation.

Functional Training Induces Greater Variety and Magnitude of Training Improvements than Traditional Resistance Training in Elderly Women.

The objective was to investigate the effects of functional (FT) and traditional (TT) training on trunk muscles maximal isometric strength, rate of force development and endurance with trained elderly women. Forty-five elderly women were directed into three groups: FT (n =1 6), TT (n = 14) and Control (n = 15). The FT (multi-planar, and multi-articular movements) and TT (primarily machine-based resistance exercises) performed mobility, muscle strength and power exercises. Both training groups also performed intermittent cardiometabolic activities. The maximum strength and endurance of the trunk muscles were verified, both at baseline and after 12 weeks of training (3xweek for 50 min each). Data were analyzed using a 2-way ANCOVA with contrast of adjusted mean values. FT significantly increased all variables: maximum trunk flexor strength (p = 0.002, 22%); rate of flexor force development (p = 0.001, 84%); trunk extensors maximal strength (p = 0.003, 17%); trunk extensor rate of force development (p = 0.05, 16%); trunk flexors (p = 0.001, 19%) and extensors (p = 0.017, 13%) endurance compared to baseline. TT showed an increase only in RFD of trunk extensors (p = 0.003, 53%), and flexors (p = 0.033, 42%), and trunk flexors endurance (p = 0.008, 11%). However, there was no statistically significant difference between groups. FT promoted improvement in all variables; strength, endurance and rate of force development of the trunk flexors and extensors of the elderly. On the other hand, TT improved only the rate of force development of trunk flexors and extensors and endurance of the trunk flexors. FT is recommended for elderly women as it improves a broader array of physiological parameters.

Ethyl Butyrate Synthesis Catalyzed by Lipases A and B from Candida antarctica Immobilized onto Magnetic Nanoparticles. Improvement of Biocatalysts' Performance under Ultrasonic Irradiation.

The synthesis of ethyl butyrate catalyzed by lipases A (CALA) or B (CALB) from Candida antarctica immobilized onto magnetic nanoparticles (MNP), CALA-MNP and CALB-MNP, respectively, is hereby reported. MNPs were prepared by co-precipitation, functionalized with 3-aminopropyltriethoxysilane, activated with glutaraldehyde, and then used as support to immobilize either CALA or CALB (immobilization yield: 100 ± 1.2% and 57.6 ± 3.8%; biocatalysts activities: 198.3 ± 2.7 Up-NPB/g and 52.9 ± 1.7 Up-NPB/g for CALA-MNP and CALB-MNP, respectively). X-ray diffraction and Raman spectroscopy analysis indicated the production of a magnetic nanomaterial with a diameter of 13.0 nm, whereas Fourier-transform infrared spectroscopy indicated functionalization, activation and enzyme immobilization. To determine the optimum conditions for the synthesis, a four-variable Central Composite Design (CCD) (biocatalyst content, molar ratio, temperature and time) was performed. Under optimized conditions (1:1, 45 °C and 6 h), it was possible to achieve 99.2 ± 0.3% of conversion for CALA-MNP (10 mg) and 97.5 ± 0.8% for CALB-MNP (12.5 mg), which retained approximately 80% of their activity after 10 consecutive cycles of esterification. Under ultrasonic irradiation, similar conversions were achieved but at 4 h of incubation, demonstrating the efficiency of ultrasound technology in the enzymatic synthesis of esters.

Immobilization of Lipase A from Candida antarctica onto Chitosan-Coated Magnetic Nanoparticles.

In this communication, lipase A from Candida antarctica (CALA) was immobilized by covalent bonding on magnetic nanoparticles coated with chitosan and activated with glutaraldehyde, labelled CALA-MNP, (immobilization parameters: 84.1% ± 1.0 for immobilization yield and 208.0 ± 3.0 U/g ± 1.1 for derivative activity). CALA-MNP biocatalyst was characterized by X-ray Powder Diffraction (XRPD), Fourier Transform Infrared (FTIR) spectroscopy, Thermogravimetry (TG) and Scanning Electron Microscope (SEM), proving the incorporation of magnetite and the immobilization of CALA in the chitosan matrix. Besides, the immobilized biocatalyst showed a half-life 8-11 times higher than that of the soluble enzyme at pH 5-9. CALA showed the highest activity at pH 7, while CALA-MNP presented the highest activity at pH 10. The immobilized enzyme was more active than the free enzyme at all studied pH values, except pH 7.