Heterologous expression and structure prediction of a xylanase identified from a compost metagenomic library.

Xylanases are key biocatalysts in the degradation of the ß-1,4-glycosidic linkages in the xylan backbone of hemicellulose. These enzymes are potentially applied in a wide range of bioprocessing industries under harsh conditions. Metagenomics has emerged as powerful tools for the bioprospection and discovery of interesting bioactive molecules from extreme ecosystems with unique features, such as high temperatures. In this study, an innovative combination of function-driven screening of a compost metagenomic library and automatic extraction of halo areas with in-house MATLAB functions resulted in the identification of a promising clone with xylanase activity (LP4). The LP4 clone proved to be an effective xylanase producer under submerged fermentation conditions. Sequence and phylogenetic analyses revealed that the xylanase, Xyl4, corresponded to an endo-1,4-ß-xylanase belonging to glycosyl hydrolase family 10 (GH10). When xyl4 was expressed in Escherichia coli BL21(DE3), the enzyme activity increased about 2-fold compared to the LP4 clone. To get insight on the interaction of the enzyme with the substrate and establish possible strategies to improve its activity, the structure of Xyl4 was predicted, refined, and docked with xylohexaose. Our data unveiled, for the first time, the relevance of the amino acids Glu133 and Glu238 for catalysis, and a close inspection of the catalytic site suggested that the replacement of Phe316 by a bulkier Trp may improve Xyl4 activity. Our current findings contribute to enhancing the catalytic performance of Xyl4 towards industrial applications. KEY POINTS: • A GH10 endo-1,4-ß-xylanase (Xyl4) was isolated from a compost metagenomic library • MATLAB's in-house functions were developed to identify the xylanase-producing clones • Computational analysis showed that Glu133 and Glu238 are crucial residues for catalysis.

[Impact of bariatric surgery on maternal-fetal outcomes during pregnancy compared to non-operated obese women]. / Impacto de la cirugía bariátrica en los resultados materno-fetales de la gestación en comparación con mujeres con obesidad no operadas.

OBJECTIVE: the aim of our study was to assess the effect of bariatric surgery on obstetric outcomes. MATERIAL AND METHODS: a retrospective cohort study was conducted, including 54 pregnancies post-bariatric surgery and 219 pregnancies in non-operated obese women, from December 2018 to January 2023. Various maternal and obstetric characteristics were evaluated, ranging from baseline data to antepartum, intrapartum, postpartum, and neonatal outcomes. RESULTS: bariatric surgery showed a significant 69 % reduction in the risk of gestational diabetes (GDM) (p = 0.045) and a 63.1 % reduction in cesarean sections (p = 0.014), but also a notable increase in the risk of miscarriage (3.5 times more, p = 0.046) and intrauterine growth restriction (35 times more, p = 0.009). Bariatric surgery was associated with a significant prolongation of postpartum hospital stay (7.5 times more, p = 0.001) and a decrease in the average weight of the newborn (213.71 g, p = 0.006). CONCLUSION: pregnancy after bariatric surgery presents benefits, such as a reduced risk of gestational diabetes (GDM) and cesarean section, but also presents challenges, such as an increased risk of miscarriage and intrauterine growth restriction (IUGR). These results highlight the importance of specialized obstetric care to optimize maternal-fetal outcomes in pregnant women with a history of bariatric surgery.

Sibling Violence and Bullying Behaviors in Peers: The Mediational Role of Self-Esteem.

In the context of the existing research on families, sibling violence is a less explored area. However, it has seemingly received more attention recently, and it can assume a relevant role in understanding the maladaptive behavior of youngsters and bullying. Additionally, adolescents involved in bullying and self-esteem are associated with disruptive violence inside the family context. This study's sample consisted of 286 students, aged between 12 and 17 years, from both sexes. This study intends to explore the association between sibling violence and bullying behavior in peers and the mediator effect of self-esteem. The measures for data collection were a demographic questionnaire, the Social Exclusion and School Violence Questionnaire, The Revised Conflict Tactics Scales (Portuguese version for siblings), and the Rosenberg Self-Esteem Scale. The results show a negative effect between negotiation in the sibling relationship (victimization) and social exclusion and verbal aggression related to bullying behavior. Self-esteem represents a total and negative mediator in this connection. Our results also show a variety of indirect outcomes amongst the negotiation dimension, psychological aggression and injury between siblings, and the social exclusion and verbal aggression dimensions (on the aggression and victimization scales). The results will be discussed according to the attachment theory but considering the importance of affective bonds with siblings as a predisposing factor to an adaptive development course.

Glucocorticoid receptor-dependent therapeutic efficacy of tauroursodeoxycholic acid in preclinical models of spinocerebellar ataxia type 3.

Spinocerebellar ataxia type 3 (SCA3) is an adult-onset neurodegenerative disease caused by a polyglutamine expansion in the ataxin-3 (ATXN3) gene. No effective treatment is available for this disorder, other than symptom-directed approaches. Bile acids have shown therapeutic efficacy in neurodegenerative disease models. Here, we pinpointed tauroursodeoxycholic acid (TUDCA) as an efficient therapeutic, improving the motor and neuropathological phenotype of SCA3 nematode and mouse models. Surprisingly, transcriptomic and functional in vivo data showed that TUDCA acts in neuronal tissue through the glucocorticoid receptor (GR), but independently of its canonical receptor, the farnesoid X receptor (FXR). TUDCA was predicted to bind to the GR, in a similar fashion to corticosteroid molecules. GR levels were decreased in disease-affected brain regions, likely due to increased protein degradation as a consequence of ATXN3 dysfunction being restored by TUDCA treatment. Analysis of a SCA3 clinical cohort showed intriguing correlations between the peripheral expression of GR and the predicted age at disease onset in presymptomatic subjects and FKBP5 expression with disease progression, suggesting this pathway as a potential source of biomarkers for future study. We have established a novel in vivo mechanism for the neuroprotective effects of TUDCA in SCA3 and propose this readily available drug for clinical trials in SCA3 patients.

Exploring Professional Practice Environments and Organisational Context Factors Affecting Nurses' Adoption of Evidence-Based Practice: A Scoping Review.

This scoping review, conducted within the Joanna Briggs Institute (JBI) framework, analysed the recent literature (January 2018 to March 2023) addressing factors inherent to professional practice environments and organisational contexts influencing nurses' adoption of evidence-based practice (EBP). This review included studies involving nurses regardless of sector, practice setting, and scope of practice. A systematic search was undertaken across the PubMed, Web of Science, CINAHL, and MEDLINE databases, as well as the EThOS, OATD, and RCAAP platforms. The extracted textual elements underwent a content analysis, resulting in a coding structure established through an inductive approach that categorised information into main categories and subcategories linked by similarity and thematic affinity. Forty-one studies were included, revealing four main categories of factors impacting EBP adoption by nurses: (1) organisational dynamics, (2) management and leadership, (3) teamwork and communication, and (4) resources and infrastructure. The study's limitations acknowledge the subjective nature of categorisation, recognising potential variations based on individual perspectives despite adopting procedures to minimise the risk of bias. The results provide a substantial foundation for developing interventions to cultivate environments conducive to EBP adoption by nurses, thereby enhancing the integration of evidence into nurses' professional practice contexts. This review was prospectively registered on the Open Science Framework (registration no. osf.io/e86qz).

Drug Discovery Based on Oxygen and Nitrogen (Non-)Heterocyclic Compounds Developed @LAQV-REQUIMTE/Aveiro.

Artur Silva's research group has a long history in the field of medicinal chemistry. The development of new synthetic methods for oxygen (mostly polyphenols, e.g., 2- and 3-styrylchromones, xanthones, flavones) and nitrogen (e.g., pyrazoles, triazoles, acridones, 4-quinolones) heterocyclic compounds in order to be assessed as antioxidant, anti-inflammatory, antidiabetic, and anticancer agents has been the main core work of our research interests. Additionally, the synthesis of steroid-type compounds as anti-Alzheimer drugs as well as of several chromophores as important dyes for cellular imaging broadened our research scope. In this review article, we intend to provide an enlightened appraisal of all the bioactive compounds and their biological properties that were synthesized and studied by our research group in the last two decades.

Metabolic and chromosomal changes in a Bacillus subtilis whiA mutant.

IMPORTANCE: WhiA is a conserved DNA-binding protein that influences cell division in many Gram-positive bacteria and, in B. subtilis, also chromosome segregation. How WhiA works in Bacillus subtilis is unknown. Here, we tested three hypothetical mechanisms using metabolomics, fatty acid analysis, and chromosome confirmation capture experiments. This revealed that WhiA does not influence cell division and chromosome segregation by modulating either central carbon metabolism or fatty acid composition. However, the inactivation of WhiA reduces short-range chromosome interactions. These findings provide new avenues to study the molecular mechanism of WhiA in the future.

Emotional Distress in Portuguese Cancer Patients: The Use of the Emotion Thermometers (ET) Screening Tool.

Cancer patients may experience significant distress. The "Emotion Thermometers" (ETs) are a short visual analogue scale used to screen patients for psychosocial risk. This study aimed to assess emotional distress in a large sample of cancer patients attending psychological services at an non-governmental organization (NGO), and to explore factors that may contribute to it. The ETs were answered by 899 cancer patients. They were, on average, 59.9 years old, the majority were female, had breast cancer, were under treatment or were disease-free survivors, and reported high levels of emotional distress, above the cut-off (≥5). A Generalized Linear Model was used to measure the association between the level of distress, age, gender, disease phase and 33 items of the problem list. Four items-sadness, depression, sleep and breathing-were found to be significantly related to a higher level of distress. Additionally, women and patients who were in the palliative phase also had significantly higher levels of distress. The results confirm the need for early emotional screening in cancer patients, as well as attending to the characteristics of each patient. Additionally, they highlight the utility of the ETs for the clinical practice, allowing to optimize the referral to specialized psychosocial services.

Peripheral Blood Serum NMR Metabolomics Is a Powerful Tool to Discriminate Benign and Malignant Ovarian Tumors.

Ovarian cancer is the major cause of death from gynecological cancer and the third most common gynecological malignancy worldwide. Despite a slight improvement in the overall survival of ovarian carcinoma patients in recent decades, the cure rate has not improved. This is mainly due to late diagnosis and resistance to therapy. It is therefore urgent to develop effective methods for early detection and prognosis. We hypothesized that, besides being able to distinguish serum samples of patients with ovarian cancer from those of patients with benign ovarian tumors, 1H-NMR metabolomics analysis might be able to predict the malignant potential of tumors. For this, serum 1H-NMR metabolomics analyses were performed, including patients with malignant, benign and borderline ovarian tumors. The serum metabolic profiles were analyzed by multivariate statistical analysis, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) methods. A metabolic profile associated with ovarian malignant tumors was defined, in which lactate, 3-hydroxybutyrate and acetone were increased and acetate, histidine, valine and methanol were decreased. Our data support the use of 1H-NMR metabolomics analysis as a screening method for ovarian cancer detection and might be useful for predicting the malignant potential of borderline tumors.

Interventions to Minimize Medication Error by Nurses in Intensive Care: A Scoping Review Protocol.

Medication errors represent a concern for healthcare organizations due to their negative consequences. In the nursing context, these errors represent a threat to the quality of care and patient safety. Many factors have been identified as potential causes for these errors in intensive care units. A scoping review will be developed to identify interventions/strategies to minimize the occurrence of medication errors by nurses, considering the Joanna Briggs Institute (JBI) methodology. A search will be conducted in the EbscoHost (CINAHL Complete and MEDLINE), Embase and PubMed databases. Data analysis, extraction and synthesis will be carried out by two reviewers independently. This review will attempt to map which interventions are more specific to minimizing medication error by nurses in intensive care and to recognize which factors influence this type of error to mitigate practices that may lead to error. This protocol acts as the framework for a scoping review in the strategy to map the interventions and which factors contribute to the medication error by intensive care nurses. This study was prospectively registered with the Open Science Framework on 21 April 2023 with registration number DOI 10.17605/OSF.IO/94KH3.

Single Modality vs. Multimodality: What Works Best for Lung Cancer Screening?

In a clinical context, physicians usually take into account information from more than one data modality when making decisions regarding cancer diagnosis and treatment planning. Artificial intelligence-based methods should mimic the clinical method and take into consideration different sources of data that allow a more comprehensive analysis of the patient and, as a consequence, a more accurate diagnosis. Lung cancer evaluation, in particular, can benefit from this approach since this pathology presents high mortality rates due to its late diagnosis. However, many related works make use of a single data source, namely imaging data. Therefore, this work aims to study the prediction of lung cancer when using more than one data modality. The National Lung Screening Trial dataset that contains data from different sources, specifically, computed tomography (CT) scans and clinical data, was used for the study, the development and comparison of single-modality and multimodality models, that may explore the predictive capability of these two types of data to their full potential. A ResNet18 network was trained to classify 3D CT nodule regions of interest (ROI), whereas a random forest algorithm was used to classify the clinical data, with the former achieving an area under the ROC curve (AUC) of 0.7897 and the latter 0.5241. Regarding the multimodality approaches, three strategies, based on intermediate and late fusion, were implemented to combine the information from the 3D CT nodule ROIs and the clinical data. From those, the best model-a fully connected layer that receives as input a combination of clinical data and deep imaging features, given by a ResNet18 inference model-presented an AUC of 0.8021. Lung cancer is a complex disease, characterized by a multitude of biological and physiological phenomena and influenced by multiple factors. It is thus imperative that the models are capable of responding to that need. The results obtained showed that the combination of different types may have the potential to produce more comprehensive analyses of the disease by the models.

Postural stability computerized evaluation in total knee arthroplasty.

PURPOSE: To evaluate the balance in patients with total knee arthroplasty (TKA) and knee osteoarthrosis (KOA), measured by postural stability computerized evaluation (PSCE), and to evaluate the effect of post-TKA patients' characteristics in their performance on PSCE. MATERIALS AND METHODS: An observational cross-sectional study was conducted in two sets of patients: (A) patients with KOA and primary TKA surgery scheduled and (B) patients who underwent primary TKA >9 months. Sociodemographic, radiographic, clinical and PSCE parameters (using the Biodex Balance System) were assessed. RESULTS: Post-TKA patients placed more load on the replaced knee than the contralateral osteoarthritic knee (p = 0.027). They had less imbalance on the balance tests performed with the eyes open, on stable (p = 0.032), and unstable platforms (p = 0.022). These patients also showed better postural stability in monopodalic stance, both standing on the TKA (p = 0.010) and contralateral knee (p = 0.017). Age, weight, pain on the operated knee, extension deficit on the operated knee, and Berg Balance Scale scores on post-TKA patients were significantly associated with their performance on PSCE tests. CONCLUSIONS: PSCE can be useful to quantify the balance of post-TKA and KOA patients.

Total knee arthroplasty is the definitive treatment for knee osteoarthrosis and it has several benefits, but its effect on balance is still unknown.Postural stability computerized evaluation is used to evaluate balance on vestibular diseases and it has been recently studied on musculoskeletal conditions.Postural stability computerized evaluation may be useful to evaluate patients' balance before and after total knee arthroplasty.

Functional and sequence-based metagenomics to uncover carbohydrate-degrading enzymes from composting samples.

The renewable, abundant , and low-cost nature of lignocellulosic biomass can play an important role in the sustainable production of bioenergy and several added-value bioproducts, thus providing alternative solutions to counteract the global energetic and industrial demands. The efficient conversion of lignocellulosic biomass greatly relies on the catalytic activity of carbohydrate-active enzymes (CAZymes). Finding novel and robust biocatalysts, capable of being active under harsh industrial conditions, is thus imperative to achieve an economically feasible process. In this study, thermophilic compost samples from three Portuguese companies were collected, and their metagenomic DNA was extracted and sequenced through shotgun sequencing. A novel multi-step bioinformatic pipeline was developed to find CAZymes and characterize the taxonomic and functional profiles of the microbial communities, using both reads and metagenome-assembled genomes (MAGs) as input. The samples' microbiome was dominated by bacteria, where the classes Gammaproteobacteria, Alphaproteobacteria, and Balneolia stood out for their higher abundance, indicating that the degradation of compost biomass is mainly driven by bacterial enzymatic activity. Furthermore, the functional studies revealed that our samples are a rich reservoir of glycoside hydrolases (GH), particularly of GH5 and GH9 cellulases, and GH3 oligosaccharide-degrading enzymes. We further constructed metagenomic fosmid libraries with the compost DNA and demonstrated that a great number of clones exhibited ß-glucosidase activity. The comparison of our samples with others from the literature showed that, independently of the composition and process conditions, composting is an excellent source of lignocellulose-degrading enzymes. To the best of our knowledge, this is the first comparative study on the CAZyme abundance and taxonomic/functional profiles of Portuguese compost samples. KEY POINTS: • Sequence- and function-based metagenomics were used to find CAZymes in compost samples. • Thermophilic composts proved to be rich in bacterial GH3, GH5, and GH9 enzymes. • Compost-derived fosmid libraries are enriched in clones with ß-glucosidase activity.

Machine learning-based approaches for cancer prediction using microbiome data.

Emerging evidence of the relationship between the microbiome composition and the development of numerous diseases, including cancer, has led to an increasing interest in the study of the human microbiome. Technological breakthroughs regarding DNA sequencing methods propelled microbiome studies with a large number of samples, which called for the necessity of more sophisticated data-analytical tools to analyze this complex relationship. The aim of this work was to develop a machine learning-based approach to distinguish the type of cancer based on the analysis of the tissue-specific microbial information, assessing the human microbiome as valuable predictive information for cancer identification. For this purpose, Random Forest algorithms were trained for the classification of five types of cancer-head and neck, esophageal, stomach, colon, and rectum cancers-with samples provided by The Cancer Microbiome Atlas database. One versus all and multi-class classification studies were conducted to evaluate the discriminative capability of the microbial data across increasing levels of cancer site specificity, with results showing a progressive rise in difficulty for accurate sample classification. Random Forest models achieved promising performances when predicting head and neck, stomach, and colon cancer cases, with the latter returning accuracy scores above 90% across the different studies conducted. However, there was also an increased difficulty when discriminating esophageal and rectum cancers, failing to differentiate with adequate results rectum from colon cancer cases, and esophageal from head and neck and stomach cancers. These results point to the fact that anatomically adjacent cancers can be more complex to identify due to microbial similarities. Despite the limitations, microbiome data analysis using machine learning may advance novel strategies to improve cancer detection and prevention, and decrease disease burden.

Learning the Biochemical Basis of Axonal Guidance: Using Caenorhabditis elegans as a Model.

AIM: Experimental models are a powerful aid in visualizing molecular phenomena. This work reports how the worm Caenorhabditis elegans (C. elegans) can be effectively explored for students to learn how molecular cues dramatically condition axonal guidance and define nervous system structure and behavior at the organism level. Summary of work: A loosely oriented observational activity preceded detailed discussions on molecules implied in axonal migration. C. elegans mutants were used to introduce second-year medical students to the deleterious effects of gene malfunctioning in neuron response to extracellular biochemical cues and to establish links between molecular function, nervous system structure, and animal behavior. Students observed C. elegans cultures and associated animal behavior alterations with the lack of function of specific axon guidance molecules (the soluble cue netrin/UNC-6 or two receptors, DCC/UNC-40 and UNC-5H). Microscopical observations of these strains, in combination with pan-neuronal GFP expression, allowed optimal visualization of severely affected neurons. Once the list of mutated genes in each strain was displayed, students could also relate abnormal patterns in axon migration/ventral and dorsal nerve cord neuron formation in C. elegans with mutated molecular components homologous to those in humans. SUMMARY OF RESULTS: Students rated the importance and effectiveness of the activity very highly. Ninety-three percent found it helpful to grasp human axonal migration, and all students were surprised with the power of the model in helping to visualize the phenomenon.

Cyclic di-AMP traps proton-coupled K+ transporters of the KUP family in an inward-occluded conformation.

Cyclic di-AMP is the only known essential second messenger in bacteria and archaea, regulating different proteins indispensable for numerous physiological processes. In particular, it controls various potassium and osmolyte transporters involved in osmoregulation. In Bacillus subtilis, the K+/H+ symporter KimA of the KUP family is inactivated by c-di-AMP. KimA sustains survival at potassium limitation at low external pH by mediating potassium ion uptake. However, at elevated intracellular K+ concentrations, further K+ accumulation would be toxic. In this study, we reveal the molecular basis of how c-di-AMP binding inhibits KimA. We report cryo-EM structures of KimA with bound c-di-AMP in detergent solution and reconstituted in amphipols. By combining structural data with functional assays and molecular dynamics simulations we reveal how c-di-AMP modulates transport. We show that an intracellular loop in the transmembrane domain interacts with c-di-AMP bound to the adjacent cytosolic domain. This reduces the mobility of transmembrane helices at the cytosolic side of the K+ binding site and therefore traps KimA in an inward-occluded conformation.

Active aging awareness and well-being among older adults in Portugal.

Objective: This study aims to assess the active aging awareness of older adults in mainland Portugal and their levels of overall well-being and to identify social and health-related factors. Methods: A cross-sectional study was conducted with a representative sample of 613 older adults, aged 65 or older, who participated in the PROKnos - Knowing Social Prescribing needs of the elderly study in Portugal. The questionnaire consisted of the Active Ageing Awareness Questionnaire and the World Health Organization - Five Well-Being Index, as well as sociodemographic, economic, and health status questions. Correlation coefficients, t-tests for independent samples, and one-way ANOVA were used to explore potential associations between variables. Results: The active aging awareness levels were significantly higher for women (p = 0.031), and those who were younger (p = 0.011), more educated (p < 0.001), had a better financial situation (p < 0.001), and had better health (p < 0.001). The same pattern was found for well-being, except in relation to gender, as men had higher levels (p = 0.016). These variables were found to be correlated. Discussion: Even though active aging is an important strategy to implement, it is indispensable to consider the perceptions and conditions that need to be in place before that. This study reveals that several social and health-related factors are associated with well-being and active aging awareness, as well as the differences between groups that exist in mainland Portugal in relation to that. This emphasizes how vital it is to address social inequalities in active aging efforts, which are not necessarily uncovered when only considering actual active aging measures.

Neurodifferentiation and Neuroprotection Potential of Mesenchymal Stromal Cell-Derived Secretome Produced in Different Dynamic Systems.

Parkinson's disease (PD) is the second most common neurodegenerative disorder and is characterized by the degeneration of the dopamine (DA) neurons in the substantia nigra pars compacta, leading to a loss of DA in the basal ganglia. The presence of aggregates of alpha-synuclein (α-synuclein) is seen as the main contributor to the pathogenesis and progression of PD. Evidence suggests that the secretome of mesenchymal stromal cells (MSC) could be a potential cell-free therapy for PD. However, to accelerate the integration of this therapy in the clinical setting, there is still the need to develop a protocol for the large-scale production of secretome under good manufacturing practices (GMP) guidelines. Bioreactors have the capacity to produce large quantities of secretomes in a scalable manner, surpassing the limitations of planar static culture systems. However, few studies focused on the influence of the culture system used to expand MSC, on the secretome composition. In this work, we studied the capacity of the secretome produced by bone marrow-derived mesenchymal stromal cells (BMSC) expanded in a spinner flask (SP) and in a Vertical-Wheel™ bioreactor (VWBR) system, to induce neurodifferentiation of human neural progenitor cells (hNPCs) and to prevent dopaminergic neuron degeneration caused by the overexpression of α-synuclein in one Caenorhabditis elegans model of PD. Results showed that secretomes from both systems were able to induce neurodifferentiation, though the secretome produced in the SP system had a greater effect. Additionally, in the conditions of our study, only the secretome produced in SP had a neuroprotective potential. Lastly, the secretomes had different profiles regarding the presence and/or specific intensity of different molecules, namely, interleukin (IL)-6, IL-4, matrix metalloproteinase-2 (MMP2), and 3 (MMP3), tumor necrosis factor-beta (TNF-ß), osteopontin, nerve growth factor beta (NGFß), granulocyte colony-stimulating factor (GCSF), heparin-binding (HB) epithelial growth factor (EGF)-like growth factor (HB-EGF), and IL-13. Overall, our results suggest that the culture conditions might have influenced the secretory profiles of cultured cells and, consequently, the observed effects. Additional studies should further explore the effects that different culture systems have on the secretome potential of PD.

Reduced Chitosan as a Strategy for Removing Copper Ions from Water.

Toxic heavy metals are priority pollutants in wastewater, commonly present in dangerous concentrations in many places across the globe. Although in trace quantities copper is a heavy metal essential to human life, in excess it causes various diseases, whereby its removal from wastewater is a necessity. Among several reported materials, chitosan is a highly abundant, non-toxic, low-cost, biodegradable polymer, comprising free hydroxyl and amino groups, that has been directly applied as an adsorbent or chemically modified to increase its performance. Taking this into account, reduced chitosan derivatives (RCDs 1-4) were synthesised by chitosan modification with salicylaldehyde, followed by imine reduction, characterised by RMN, FTIR-ATR, TGA and SEM, and used to adsorb Cu(II) from water. A reduced chitosan (RCD3), with a moderate modification percentage (43%) and a high imine reduction percentage (98%), proved to be more efficient than the remainder RCDs and even chitosan, especially at low concentrations under the best adsorption conditions (pH 4, RS/L = 2.5 mg mL-1). RCD3 adsorption data were better described by the Langmuir-Freundlich isotherm and the pseudo-second-order kinetic models. The interaction mechanism was assessed by molecular dynamics simulations, showing that RCDs favour Cu(II) capture from water compared to chitosan, due to a greater Cu(II) interaction with the oxygen of the glucosamine ring and the neighbouring hydroxyl groups.

Intake of added sugar, fruits, vegetables, and legumes of Portuguese preschool children: Baseline data from SmartFeeding4Kids randomized controlled trial participants.

Introduction: The SmartFeeding4Kids (SF4K) program is an online self-guided intervention for parents with the propose of changing parental feeding practices and children's dietary intake, focusing on the intake of added sugars, fruit, vegetables, and legumes. This paper aims to describe children's dietary pattern at baseline through a 24-h food recall, the SmartKidsDiet24. Methods: Overall, 89 participants recorded at least one meal of the 3-day food recall. Mean age was 36.22 ± 6.05 years and 53.09 ± 15.42 months old for parents and children, respectively. Of these, 22 participants were considered to have 2 days of near complete 24-h food recalls. Children's dietary intake are reported for these 22 participants based on parents reports and, thus, represent estimations only, as it remains unknown whether children consumed other non-reported foods. Results: Fruit was the group with the highest daily intake among children (mean 1.77 ± 1.10 portions/day), followed by added sugar foods (mean 1.48 ± 0.89 portions/day), vegetables [median 1.27 (1.64) portions/day] and legumes [median 0.12 (0.39) portions/day]. Fruit intake was positively correlated with vegetable intake (p = 0.008). Regarding Dietary Reference Values accomplishment, 13.6% of children exceeded the daily safe and adequate intake of sodium, 77.3% did not meet potassium and fiber recommendations, and 31.8% did not meet vitamin C recommendations. Discussion: All children did not meet calcium, vitamin B12 and vitamin D intake recommendations. Our findings further justify the need for dietary interventions in this field, to improve young children's diets. Clinical trial registration: ClinicalTrials.gov, identifier NCT04591496.