Energetic characterization of biomass allows for assessing its energy potential for application in different conversion processes into energy. The objective of this study is to physicochemically ...characterize pineapple crown leaves (PC) for their application in energy conversion processes. PC was characterized according to ASTM E871-82, E1755-01, and E873-82 for determination of moisture, ash, and volatile matter, respectively; the fixed carbon was calculated by difference. Higher heating value was determined by ASTM E711-87 and ash chemical composition was determined by XRF. The thermogravimetric and FTIR analyses were performed to evaluate the thermal decomposition and identify the main functional groups of biomass. PC has potential for application in thermochemical processes, showing high volatile matter (89.5 %), bulk density (420.8 kg/m³), and higher heating value (18.9 MJ/kg). The results show its energy potential justifying application of this agricultural waste into energy conversion processes, implementing sustainability in the production, and reducing the environmental liabilities caused by its disposal.
The present study aimed to investigate the physiological response to CrossFit "workouts of the day" (WODs) based on two different structures of training session: 1) the "as many repetitions as ...possible" (AMRAP) "Cindy" and 2) the "round for time" (RFT) "Open 18.4" session. CrossFit athletes (11 men and 12 women) were divided into two groups: 1) one performing the WOD "Cindy" (GC) and 2) one performing the WOD "Open 18.4" (GO). Before, immediately after and 30 min after WODs, blood lactate (LAC), heart rate (HR) and systolic and diastolic blood pressures (SBP and DBP) were measured. A two-way ANOVA indicated differences in physiological responses between GC and GO. Both WODs increased HR to similar levels. Only GO significantly increased SBP immediately after exercise compared to the rest period (
< 0.01), with no difference to GC. GO presented higher levels of LAC immediately after exercise compared to GC (15.8 ± 4.9 mM GO vs 9.3 ± 2.3 mM GC;
< 0.01). LAC remained different between the groups 30 min after exercise (7.0 ± 3.9 mM GO vs 3.9 ± 0.9 mM GC;
< 0.01). The results suggest that the studied WODs do not differ in acute cardiovascular responses, but depend on different metabolic demands, with RFT structure relying more on glycolytic metabolism (indicated by greater LAC levels after exercise in GO). Such results are in agreement independent of gender.
Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their ...native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.
High inspiratory oxygen fraction ( FIO2) may improve tissue oxygenation but also impair pulmonary function. We aimed to assess whether the use of high intraoperative FIO2 increases the risk of major ...respiratory complications.
We studied patients undergoing non-cardiothoracic surgery involving mechanical ventilation in this hospital-based registry study. The cases were divided into five groups based on the median FIO2 between intubation and extubation. The primary outcome was a composite of major respiratory complications (re-intubation, respiratory failure, pulmonary oedema, and pneumonia) developed within 7 days after surgery. Secondary outcomes included 30-day mortality. Several predefined covariates were included in a multivariate logistic regression model.
The primary analysis included 73 922 cases, of whom 3035 (4.1%) developed a major respiratory complication within 7 days of surgery. For patients in the high- and low-oxygen groups, the median FIO2 was 0.79 range 0.64–1.00 and 0.31 0.16–0.34, respectively. Multivariate logistic regression analysis revealed that the median FIO2 was associated in a dose-dependent manner with increased risk of respiratory complications (adjusted odds ratio for high vs low FIO2 1.99, 95% confidence interval 1.72–2.31, P-value for trend <0.001). This finding was robust in a series of sensitivity analyses including adjustment for intraoperative oxygenation. High median FIO2 was also associated with 30-day mortality (odds ratio for high vs low FIO2 1.97, 95% confidence interval 1.30–2.99, P-value for trend <0.001).
In this analysis of administrative data on file, high intraoperative FIO2 was associated in a dose-dependent manner with major respiratory complications and with 30-day mortality. The effect remained stable in a sensitivity analysis controlled for oxygenation.
NCT02399878.
Nanotechnology has brought great advances to many fields of modern science. A manifold of applications of nanoparticles have been found due to their interesting optical, electrical, and ...biological/chemical properties. However, the potential toxic effects of nanoparticles to different ecosystems are of special concern nowadays. Despite the efforts of the scientific community, the mechanisms of toxicity of nanoparticles are still poorly understood. Quantitative-structure activity/toxicity relationships (QSAR/QSTR) models have just started being useful computational tools for the assessment of toxic effects of nanomaterials. But most QSAR/QSTR models have been applied so far to predict ecotoxicity against only one organism/bio-indicator such as Daphnia magna. This prevents having a deeper knowledge about the real ecotoxic effects of nanoparticles, and consequently, there is no possibility to establish an efficient risk assessment of nanomaterials in the environment. In this work, a perturbation model for nano-QSAR problems is introduced with the aim of simultaneously predicting the ecotoxicity of different nanoparticles against several assay organisms (bio-indicators), by considering also multiple measures of ecotoxicity, as well as the chemical compositions, sizes, conditions under which the sizes were measured, shapes, and the time during which the diverse assay organisms were exposed to nanoparticles. The QSAR-perturbation model was derived from a database containing 5520 cases (nanoparticle–nanoparticle pairs), and it was shown to exhibit accuracies of ca. 99% in both training and prediction sets. In order to demonstrate the practical applicability of our model, three different nickel-based nanoparticles (Ni) with experimental values reported in the literature were predicted. The predictions were found to be in very good agreement with the experimental evidences, confirming that Ni-nanoparticles are not ecotoxic when compared with other nanoparticles. The results of this study thus provide a single valuable tool toward an efficient prediction of the ecotoxicity of nanoparticles under multiple experimental conditions.
•A QSAR-perturbation model was created to predict ecotoxicity of nanoparticles.•Ecotoxicities were predicted under multiple sets of experimental conditions.•Physicochemical interpretations of the descriptors were provided.•The QSAR-perturbation was used to predict new nickel-based nanoparticles.•Strong agreement existed between the theoretical predictions and the experiments.
Water pollution has generated the need to develop technologies to remove industrial pollutants. Adsorption has been recognized as one of the most effective techniques for effluent remediation. In ...this study, parts (stem and leaves) of a problematic aquatic weed, the water hyacinth (Eichhornia crassipes), were separated to produce a bioadsorbent. The objective was to evaluate the adsorption of a cationic dye, methylene blue (MB), in an aqueous solution of the biomass from different parts of the water hyacinth (Eichhornia crassipes) plants. The materials were characterized through techniques of infrared spectroscopy, scanning electron microscopy, X-ray diffractometry, and thermogravimetric analysis, before and after the material adsorption. Water hyacinth biomasses presented adsorption capacity above 89%, and the kinetics was faster for stem biomass. The kinetic study found that the adsorption process is better described by the pseudo-second-order model, and the adjustments of the isotherm experimental data indicated that both materials are favorable for adsorption. Therefore, water hyacinth bioadsorbent represents a renewable resource with potential for effluent treatment.
IntroductionVarious mechanisms have been identified to explain the relationship between gender-based violence, screening, and cancer. Biological mechanisms, primarily related to chronic stress and ...allostatic load, have been associated with high rates of chronic diseases among victims of violence, impairing the functioning of the immune and endocrine systems. Victims of abuse simultaneously show less initiative for screening exams, such as mammograms, as they perceive them as invasive and retraumatizing. They also demonstrate a greater tendency toward maladaptive coping behaviors and unhealthy lifestyles, such as abusive substance use. A significant number of these patients develop psychosocial dysfunction and body image disturbance during breast cancer treatments.ObjectivesThis work aims to provide a descriptive and narrative analysis of body image and psychosocial changes in women breast cancer survivors with prolonged experiences of violence, supported by a non-systematic literature review on the central aspects under study.MethodsFor the introductory literature review, a search was conducted on search engines such as Google Scholar and PubMed, with no date limitations, using the following terms (or combinations): “intimate partner violence,” “violence AND cancer,” “body image AND psychossexual adjustment AND breast cancer.” Additionally, a narrative analysis of body image and psychosocial changes in women breast cancer survivors with prolonged experiences of violence was conducted. For this purpose, participants were asked to complete two validated scales in the Portuguese language, and first-person testimonials were collected.ResultsThe analysis of scale results and participant testimonials highlights a consensus on the significant impairment of psychosocial functioning and the experience of sexuality. There is evidence of avoidance behaviors in terms of affectionate and sexual contact due to feelings of fear, shame, and discomfort. The breast is valued as a sensual, erotic, and essential sexual element, and impactful changes in body image persist. However, in some cases, these changes are experienced as transformative and liberating, fostering a more generous view of the body, identity, and femininity.ConclusionsWomen with breast cancer should be screened for the possibility of being victims of violence, as this context predicts a higher likelihood of emotional difficulties during surgical treatments, including psychological distress, post-traumatic stress, body shame, and self-blame. A significant number of women, including those in this study, consider the approach to self-image and sexuality in oncology consultations deficient. Psychological programs and interventions should be developed to empower patients to adjust to the sexual changes arising from treatments and disease progression and to promote positive intimate relationships and effective communication.Disclosure of InterestNone Declared
G-Protein coupled receptors (GPCRs) are involved in a myriad of pathways key for human physiology through the formation of complexes with intracellular partners such as G-proteins and arrestins ...(Arrs). However, the structural and dynamical determinants of these complexes are still largely unknown. Herein, we developed a computational big-data pipeline that enables the structural characterization of GPCR complexes with no available structure. This pipeline was used to study a well-known group of catecholamine receptors, the human dopamine receptor (DXR) family and its complexes, producing novel insights into the physiological properties of these important drug targets. A detailed description of the protein interfaces of all members of the DXR family (D1R, D2R, D3R, D4R, and D5R) and the corresponding protein interfaces of their binding partners (Arrs: Arr2 and Arr3; G-proteins: Gi1, Gi2, Gi3, Go, Gob, Gq, Gslo, Gssh, Gt2, and Gz) was generated. To produce reliable structures of the DXR family in complex with either G-proteins or Arrs, we performed homology modeling using as templates the structures of the β2-adrenergic receptor (β2AR) bound to Gs, the rhodopsin bound to Gi, and the recently acquired neurotensin receptor-1 (NTSR1) and muscarinic 2 receptor (M2R) bound to arrestin (Arr). Among others, the work demonstrated that the three partner groups, Arrs and Gs- and Gi-proteins, are all structurally and dynamically distinct. Additionally, it was revealed the involvement of different structural motifs in G-protein selective coupling between D1- and D2-like receptors. Having constructed and analyzed 50 models involving DXR, this work represents an unprecedented large-scale analysis of GPCR-intracellular partner interface determinants. All data is available at www.moreiralab.com/resources/dxr.
Nowadays, the interest in the search for new nanomaterials with improved electrical, optical, catalytic and biological properties has increased. Despite the potential benefits that can be gathered ...from the use of nanoparticles, only little attention has been paid to their possible toxic effects that may affect human health. In this context, several assays have been carried out to evaluate the cytotoxicity of nanoparticles in mammalian cells. Owing to the cost in both resources and time involved in such toxicological assays, there has been a considerable increase in the interest towards alternative computational methods, like the application of quantitative structure-activity/toxicity relationship (QSAR/QSTR) models for risk assessment of nanoparticles. However, most QSAR/QSTR models developed so far have predicted cytotoxicity against only one cell line, and they did not provide information regarding the influence of important factors rather than composition or size. This work reports a QSTR-perturbation model aiming at simultaneously predicting the cytotoxicity of different nanoparticles against several mammalian cell lines, and also considering different times of exposure of the cell lines, as well as the chemical composition of nanoparticles, size, conditions under which the size was measured, and shape. The derived QSTR-perturbation model, using a dataset of 1681 cases (nanoparticle-nanoparticle pairs), exhibited an accuracy higher than 93% for both training and prediction sets. In order to demonstrate the practical applicability of our model, the cytotoxicity of different silica (SiO2), nickel (Ni), and nickel(ii) oxide (NiO) nanoparticles were predicted and found to be in very good agreement with experimental reports. To the best of our knowledge, this is the first attempt to simultaneously predict the cytotoxicity of nanoparticles under multiple experimental conditions by applying a single unique QSTR model.
PDF
