piscesCSM: prediction of anticancer synergistic drug combinations.

While drug combination therapies are of great importance, particularly in cancer treatment, identifying novel synergistic drug combinations has been a challenging venture. Computational methods have emerged in this context as a promising tool for prioritizing drug combinations for further evaluation, though they have presented limited performance, utility, and interpretability. Here, we propose a novel predictive tool, piscesCSM, that leverages graph-based representations to model small molecule chemical structures to accurately predict drug combinations with favourable anticancer synergistic effects against one or multiple cancer cell lines. Leveraging these insights, we developed a general supervised machine learning model to guide the prediction of anticancer synergistic drug combinations in over 30 cell lines. It achieved an area under the receiver operating characteristic curve (AUROC) of up to 0.89 on independent non-redundant blind tests, outperforming state-of-the-art approaches on both large-scale oncology screening data and an independent test set generated by AstraZeneca (with more than a 16% improvement in predictive accuracy). Moreover, by exploring the interpretability of our approach, we found that simple physicochemical properties and graph-based signatures are predictive of chemotherapy synergism. To provide a simple and integrated platform to rapidly screen potential candidate pairs with favourable synergistic anticancer effects, we made piscesCSM freely available online at https://biosig.lab.uq.edu.au/piscescsm/ as a web server and API. We believe that our predictive tool will provide a valuable resource for optimizing and augmenting combinatorial screening libraries to identify effective and safe synergistic anticancer drug combinations. SCIENTIFIC CONTRIBUTION: This work proposes piscesCSM, a machine-learning-based framework that relies on well-established graph-based representations of small molecules to identify and provide better predictive accuracy of syngenetic drug combinations. Our model, piscesCSM, shows that combining physiochemical properties with graph-based signatures can outperform current architectures on classification prediction tasks. Furthermore, implementing our tool as a web server offers a user-friendly platform for researchers to screen for potential synergistic drug combinations with favorable anticancer effects against one or multiple cancer cell lines.

Fabrication and Characterization of Porous PEGDA Hydrogels for Articular Cartilage Regeneration.

Functional articular cartilage regeneration remains an unmet medical challenge, increasing the interest for innovative biomaterial-based tissue engineering (TE) strategies. Hydrogels, 3D macromolecular networks with hydrophilic groups, present articular cartilage-like features such as high water content and load-bearing capacity. In this study, 3D porous polyethylene glycol diacrylate (PEGDA) hydrogels were fabricated combining the gas foaming technique and a UV-based crosslinking strategy. The 3D porous PEGDA hydrogels were characterized in terms of their physical, structural and mechanical properties. Our results showed that the size of the hydrogel pores can be modulated by varying the initiator concentration. In vitro cytotoxicity tests showed that 3D porous PEGDA hydrogels presented high biocompatibility both with human chondrocytes and osteoblast-like cells. Importantly, the 3D porous PEGDA hydrogels supported the viability and chondrogenic differentiation of human bone marrow-derived mesenchymal stem/stromal cell (hBM-MSC)-based spheroids as demonstrated by the positive staining of typical cartilage extracellular matrix (ECM) (glycosaminoglycans (GAGs)) and upregulation of chondrogenesis marker genes. Overall, the produced 3D porous PEGDA hydrogels presented cartilage-like mechanical properties and supported MSC spheroid chondrogenesis, highlighting their potential as suitable scaffolds for cartilage TE or disease modelling strategies.

MTR3D-AF2: Expanding the coverage of spatially derived missense tolerance scores across the human proteome using AlphaFold2.

The missense tolerance ratio (MTR) was developed as a novel approach to assess the deleteriousness of variants. Its three-dimensional successor, MTR3D, was demonstrated powerful at discriminating pathogenic from benign variants. However, its reliance on experimental structures and homologs limited its coverage of the proteome. We have now utilized AlphaFold2 models to develop MTR3D-AF2, which covers 89.31% of proteins and 85.39% of residues across the human proteome. This work has improved MTR3D's ability to distinguish clinically established pathogenic from benign variants. MTR3D-AF2 is freely available as an interactive web server at https://biosig.lab.uq.edu.au/mtr3daf2/.

EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.

Nuclear magnetic resonance (NMR) crystallography is one of the main methods in structural biology for analyzing protein stereochemistry and structure. The chemical shift of the resonance frequency reflects the effect of the protons in a molecule producing distinct NMR signals in different chemical environments. Apprehending chemical shifts from NMR signals can be challenging since having an NMR structure does not necessarily provide all the required chemical shift information, making predictive models essential for accurately deducing chemical shifts, either from protein structures or, more ideally, directly from amino acid sequences. Here, we present EFG-CS, a web server that specializes in chemical shift prediction. EFG-CS employs a machine learning-based transfer prediction model for backbone atom chemical shift prediction, using ESMFold-predicted protein structures. Additionally, ESG-CS incorporates a graph neural network-based model to provide comprehensive side-chain atom chemical shift predictions. Our method demonstrated reliable performance in backbone atom prediction, achieving comparable accuracy levels with root mean square errors (RMSE) of 0.30 ppm for H, 0.22 ppm for Hα, 0.89 ppm for C, 0.89 ppm for Cα, 0.84 ppm for Cß, and 1.69 ppm for N. Moreover, our approach also showed predictive capabilities in side-chain atom chemical shift prediction achieving RMSE values of 0.71 ppm for Hß, 0.74-1.15 ppm for Hδ, and 0.58-0.94 ppm for Hγ, solely utilizing amino acid sequences without homology or feature curation. This work shows for the first time that generative AI protein models can predict NMR shifts nearly comparable to experimental models. This web server is freely available at https://biosig.lab.uq.edu.au/efg_cs, and the chemical shift prediction results can be downloaded in tabular format and visualized in 3D format.

Sexuality and sexual dysfunction in patients with psoriatic arthritis: A cross-sectional study.

OBJECTIVE: Psoriatic arthritis (PsA) is a chronic inflammatory disorder affecting the joints, skin and entheses. Despite the importance of the topic, few studies have investigated the association between PsA and sexual function. The purpose of this study was to assess sexuality and the prevalence of sexual dysfunction (SD) in patients with PsA. METHODS: This was an observational, cross-sectional single-center study on 23 PsA patients (male=12; female=11) evaluated with 2 male questionnaires (MSQ= Male Sexual Quotient, and IIEF=International Index of Erectile Function) and 2 female questionnaires (FSQ= Female Sexual Quotient, and FSFI=Female Sexual Function Index) validated for Brazilian Portuguese, in order to determine changes in sexual function. Clinical parameters, musculoskeletal activity and skin activity were also analyzed to identify factors associated with SD. RESULTS: The mean age was 52.1±9.7 years (males) and 49.1±9.6 years (females). Clinically, the patients had low skin and peripheral joint disease activity or were in remission. The mean time of PsA was 10±6.2 years, and 65.2% had a steady sexual partner. The mean MSQ score was 75.8±16.8. The prevalence of SD was 91.7% in men (IIEF), with a predominance of mild SD. The mean FSQ score was 64.9±24.1. The prevalence of SD was 72.7% in women (FSFI), with low domain scores. Also, a significant association was found between female age and total and domain-specific FSFI scores. PASI (Psoriasis Area and Severity Index) and the general satisfaction domain (IIEF) were significantly correlated. CONCLUSION: This study found a high prevalence of SD in PsA patients. Age had a negative impact on female sexual function. Physicians need to be more aware of SD in this population to provide early multidisciplinary treatment and minimize the impact of the disease on the quality of life of patients and their partners.

The implications of industry 4.0 for the tourism sector: A systematic literature review.

The tourism sector is presently facing new challenges resulting from the increasing digitalization of society. Boosted by industry 4.0, new tourism dynamics are emerging. Nonetheless, the real significance of this revolutionary trend and its implications still lack further development. Aiming to assess the state-of-the-art about the digital transformation on the tourism sector, triggered by the 4.0 paradigm, the present study followed a systematic literature review approach, adopting the PRISMA protocol guidelines. A total of 44 manuscripts were considered relevant for analysis. The findings illustrate that the 4.0 paradigm is being embraced from three main perspectives: the visitor-technology interaction and its influence on decision-making, the digital competencies in tourism students, and the technology penetration in different sub-sectors of the supply chain. However, studies conceptualizing the 4.0 paradigm in the tourism sector are lacking, beyond empirical research on areas such as digital skills, pros and cons of industry 4.0 technologies, and spatial consequences.

DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.

Protein-protein interactions (PPIs) play a vital role in cellular functions and are essential for therapeutic development and understanding diseases. However, current predictive tools often struggle to balance efficiency and precision in predicting the effects of mutations on these complex interactions. To address this, we present DDMut-PPI, a deep learning model that efficiently and accurately predicts changes in PPI binding free energy upon single and multiple point mutations. Building on the robust Siamese network architecture with graph-based signatures from our prior work, DDMut, the DDMut-PPI model was enhanced with a graph convolutional network operated on the protein interaction interface. We used residue-specific embeddings from ProtT5 protein language model as node features, and a variety of molecular interactions as edge features. By integrating evolutionary context with spatial information, this framework enables DDMut-PPI to achieve a robust Pearson correlation of up to 0.75 (root mean squared error: 1.33 kcal/mol) in our evaluations, outperforming most existing methods. Importantly, the model demonstrated consistent performance across mutations that increase or decrease binding affinity. DDMut-PPI offers a significant advancement in the field and will serve as a valuable tool for researchers probing the complexities of protein interactions. DDMut-PPI is freely available as a web server and an application programming interface at https://biosig.lab.uq.edu.au/ddmut_ppi.

Py-CoMFA, docking, and molecular dynamics simulations of Leishmania (L.) amazonensis arginase inhibitors.

Leishmaniasis is a disease caused by a protozoan of the genus Leishmania, affecting millions of people, mainly in tropical countries, due to poor social conditions and low economic development. First-line chemotherapeutic agents involve highly toxic pentavalent antimonials, while treatment failure is mainly due to the emergence of drug-resistant strains. Leishmania arginase (ARG) enzyme is vital in pathogenicity and contributes to a higher infection rate, thus representing a potential drug target. This study helps in designing ARG inhibitors for the treatment of leishmaniasis. Py-CoMFA (3D-QSAR) models were constructed using 34 inhibitors from different chemical classes against ARG from L. (L.) amazonensis (LaARG). The 3D-QSAR predictions showed an excellent correlation between experimental and calculated pIC50 values. The molecular docking study identified the favorable hydrophobicity contribution of phenyl and cyclohexyl groups as substituents in the enzyme allosteric site. Molecular dynamics simulations of selected protein-ligand complexes were conducted to understand derivatives' interaction modes and affinity in both active and allosteric sites. Two cinnamide compounds, 7g and 7k, were identified, with similar structures to the reference 4h allosteric site inhibitor. These compounds can guide the development of more effective arginase inhibitors as potential antileishmanial drugs.

Evaluation of Silybin Nanoparticles against Liver Damage in Murine Schistosomiasis mansoni Infection.

Silybin (SIB) is a hepatoprotective drug known for its poor oral bioavailability, attributed to its classification as a class IV drug with significant metabolism during the first-pass effect. This study explored the potential of solid lipid nanoparticles with (SLN-SIB-U) or without (SLN-SIB) ursodeoxycholic acid and polymeric nanoparticles (PN-SIB) as delivery systems for SIB. The efficacy of these nanosystems was assessed through in vitro studies using the GRX and Caco-2 cell lines for permeability and proliferation assays, respectively, as well as in vivo experiments employing a murine model of Schistosomiasis mansoni infection in BALB/c mice. The mean diameter and encapsulation efficiency of the nanosystems were as follows: SLN-SIB (252.8 ± 4.4 nm, 90.28 ± 2.2%), SLN-SIB-U (252.9 ± 14.4 nm, 77.05 ± 2.8%), and PN-SIB (241.8 ± 4.1 nm, 98.0 ± 0.2%). In the proliferation assay with the GRX cell line, SLN-SIB and SLN-SIB-U exhibited inhibitory effects of 43.09 ± 5.74% and 38.78 ± 3.78%, respectively, compared to PN-SIB, which showed no inhibitory effect. Moreover, SLN-SIB-U demonstrated a greater apparent permeability coefficient (25.82 ± 2.2) than PN-SIB (20.76 ± 0.1), which was twice as high as that of SLN-SIB (11.32 ± 4.6) and pure SIB (11.28 ± 0.2). These findings suggest that solid lipid nanosystems hold promise for further in vivo investigations. In the murine model of acute-phase Schistosomiasis mansoni infection, both SLN-SIB and SLN-SIB-U displayed hepatoprotective effects, as evidenced by lower alanine amino transferase values (22.89 ± 1.6 and 23.93 ± 2.4 U/L, respectively) than those in control groups I (29.55 ± 0.7 U/L) and I+SIB (34.29 ± 0.3 U/L). Among the prepared nanosystems, SLN-SIB-U emerges as a promising candidate for enhancing the pharmacokinetic properties of SIB.

Statine-based peptidomimetic compounds as inhibitors for SARS-CoV-2 main protease (SARS-CoV­2 Mpro).

COVID-19 is a multisystemic disease caused by the SARS-CoV-2 airborne virus, a member of the Coronaviridae family. It has a positive sense single-stranded RNA genome and encodes two non-structural proteins through viral cysteine-proteases processing. Blocking this step is crucial to control virus replication. In this work, we reported the synthesis of 23 statine-based peptidomimetics to determine their ability to inhibit the main protease (Mpro) activity of SARS-CoV-2. Among the 23 peptidomimetics, 15 compounds effectively inhibited Mpro activity by 50% or more, while three compounds (7d, 8e, and 9g) exhibited maximum inhibition above 70% and IC50 < 1 µM. Compounds 7d, 8e, and 9g inhibited roughly 80% of SARS-CoV-2 replication and proved no cytotoxicity. Molecular docking simulations show putative hydrogen bond and hydrophobic interactions between specific amino acids and these inhibitors. Molecular dynamics simulations further confirmed the stability and persisting interactions in Mpro's subsites, exhibiting favorable free energy binding (ΔGbind) values. These findings suggest the statine-based peptidomimetics as potential therapeutic agents against SARS-CoV-2 by targeting Mpro.

Novel naphthoquinone-1H-1,2,3-triazole hybrids: Design, synthesis and evaluation as inductors of ROS-mediated apoptosis in the MCF-7 cells.

The search for novel anticancer drugs is essential to expand treatment options, overcome drug resistance, reduce toxicity, promote innovation, and tackle the economic impact. The importance of these studies lies in their contribution to advancing cancer research and enhancing patient outcomes in the battle against cancer. Here, we developed new asymmetric hybrids containing two different naphthoquinones linked by a 1,2,3-1H-triazole nucleus, which are potential new drugs for cancer treatment. The antitumor activity of the novel compounds was tested using the breast cancer cell lines MCF-7 and MDA-MB-231, using the non-cancer cell line MCF10A as control. Our results showed that two out of twenty-two substances tested presented potential antitumor activity against the breast cancer cell lines. These potential drugs, named here 12g and 12h were effective in reducing cell viability and promoting cell death of the tumor cell lines, exhibiting minimal effects on the control cell line. The mechanism of action of the novel drugs was assessed revealing that both drugs increased reactive oxygen species production with consequent activation of the AMPK pathway. Therefore, we concluded that 12g and 12h are novel AMPK activators presenting selective antitumor effects.

Clinical outcome and prognosis of patients with acute myeloid leukemia submitted to chemotherapy with 5 years of follow-up

Abstract Objective The purpose of this study was to evaluate the clinical-epidemiological profile, associated risk factors and clinical outcomes of patients with acute myeloid leukemia (AML), identifying the main causes of morbidity and mortality and overall survival rate of patients at five years of follow-up. Method This was a retrospective cohort study evaluating the prognosis and clinical outcomes of 222 patients diagnosed with AML at three large hematology centers in Ceará (northeastern Brazil) over a period of five years. Results The mean age at diagnosis was 44.1 ± 16 years, with a female prevalence of 1.3:1. No additional relevant risk factors associated with the development of AML were found, except for the well-established cytogenetic assessment. The overall 5-year survival rate was 39.4% (95%CI: 35.47 - 42.17). The main causes of death were disease progression (37.72%; n = 84) and sepsis (31.58%; n = 70). Conclusion The clinical outcomes in our sample of AML patients were similar to those of other reported groups. Disease progression and infection were the main causes of death. Access to diagnostic flow cytometry and karyotyping was greater in our sample than in the national average. As expected, overall survival differed significantly according to the risk, as determined by cytogenetic testing.

Unsupervised analysis of whole transcriptome data from human pluripotent stem cells cardiac differentiation.

The main objective of the present work was to highlight differences and similarities in gene expression patterns between different pluripotent stem cell cardiac differentiation protocols, using a workflow based on unsupervised machine learning algorithms to analyse the transcriptome of cells cultured as a 2D monolayer or as 3D aggregates. This unsupervised approach effectively allowed to portray the transcriptomic changes that occurred throughout the differentiation processes, with a visual representation of the entire transcriptome. The results allowed to corroborate previously reported data and also to unveil new gene expression patterns. In particular, it was possible to identify a correlation between low cardiomyocyte differentiation efficiencies and the early expression of a set of non-mesodermal genes, which can be further explored as predictive markers of differentiation efficiency. The workflow here developed can also be applied to analyse other stem cell differentiation transcriptomic datasets, envisaging future clinical implementation of cellular therapies.

N, N'-disubstituted Ureas as Novel Antiplatelet Agents: Synthesis, Pharmacological Evaluation and In Silico Studies.

INTRODUCTION: Thrombotic disorders are among the leading causes of morbidity and mortality worldwide. Drugs used in the prevention and treatment of atherothrombosis have pharmacokinetic limitations and adverse effects such as hemorrhagic conditions, highlighting the importance of developing more effective antiplatelet agents. ethod: In this work, we synthesized N,N'-disubstituted ureas 3a-3j and evaluated their antiplatelet profiles through in vitro, ex vivo, and in silico studies. The synthesized derivatives exhibited a selective inhibitory profile against platelet aggregation induced by arachidonic acid (AA) in vitro, without significantly affecting other aspects of primary hemostasis and blood coagulation. The compounds that showed inhibition greater than 85% were submitted to the analysis of their potency by calculating the concentration required to inhibit 50% of platelet aggregation induced by AA (IC50). Urea derivative 3a was the most potent with IC50 of 1.45 µM. Interestingly, this derivative inhibited more than 90% of platelet aggregation induced by AA ex vivo, with a similar effect to acetylsalicylic acid. In the hemolysis assay, most of the urea derivatives presented values below 10% suggesting good hemocompatibility. Additionally, the compounds tested at 100 µM also showed no cytotoxic effects in HepG2 and Vero cells. RESULT: The in silico results suggested that compound 3a may bind to the key residue of COX-1 similar to AA and known COX-1 inhibitors, and the results are also in agreement with our SAR, which suggests that the inhibition of this enzyme is the most likely mechanism of antiplatelet activity. CONCLUSION: Therefore, these results demonstrated that N,N'-disubstituted ureas are promising candidates for the development of novel antiplatelet agents.

Exploring the effects of missense mutations on protein thermodynamics through structure-based approaches: findings from the CAGI6 challenges.

Missense mutations are known contributors to diverse genetic disorders, due to their subtle, single amino acid changes imparted on the resultant protein. Because of this, understanding the impact of these mutations on protein stability and function is crucial for unravelling disease mechanisms and developing targeted therapies. The Critical Assessment of Genome Interpretation (CAGI) provides a valuable platform for benchmarking state-of-the-art computational methods in predicting the impact of disease-related mutations on protein thermodynamics. Here we report the performance of our comprehensive platform of structure-based computational approaches to evaluate mutations impacting protein structure and function on 3 challenges from CAGI6: Calmodulin, MAPK1 and MAPK3. Our stability predictors have achieved correlations of up to 0.74 and AUCs of 1 when predicting changes in ΔΔG for MAPK1 and MAPK3, respectively, and AUC of up to 0.75 in the Calmodulin challenge. Overall, our study highlights the importance of structure-based approaches in understanding the effects of missense mutations on protein thermodynamics. The results obtained from the CAGI6 challenges contribute to the ongoing efforts to enhance our understanding of disease mechanisms and facilitate the development of personalised medicine approaches.

Cartografia das estratégias utilizadas para o trabalho colaborativo em equipes de saúde da família / Cartografía de las estrategias utilizadas para el trabajo colaborativo en equipos de salud de la familia / Strategies used for collaborative work in family health teams: a cartographic analysis

O estudo objetivou mapear as estratégias utilizadas para o trabalho colaborativo em equipes de Saúde da Família (eSF) inseridas na Atenção Primária à Saúde (APS), em um município do norte de Minas. Trata-se de um estudo qualitativo, com a proposta metodológica da Cartografia. Os dados foram produzidos em quatro eSF por meio de observação participante, questionário de identificação, diário cartográfico, entrevista semiestruturada individual e grupo focal. A análise do discurso e o rastreio cartográfico possibilitaram a construção de duas categorias temáticas e um mapa cartográfico. Alcançou-se que as estratégias, consideradas linhas de fuga, permitem transformações existenciais no trabalho em equipe, pois originam nascentes em solos cristalizados, pensamentos problematizadores, subjetividade e interações disciplinares. Concluiu-se que as linhas duras não devem ser eliminadas do trabalho em equipe, pois coexistem nessa realidade, e o que importa é como são vivenciadas nas relações.

El objetivo del estudio fue mapear las estrategias utilizadas para el trabajo colaborativo en equipos de Salud de la Familia (eSF), inseridas en la Atención Primaria de la Salud, en un municipio del Norte de Minas Gerais. Se trata de un estudio cualitativo, con la propuesta metodológica de la Cartografía. Los datos se produjeron en cuatro eSF, por medio de observación participativa, cuestionario de identificación, diario cartográfico, entrevista semiestructurada individual y grupo focal. El análisis del discurso y el rastreo cartográfico posibilitaron la construcción de dos categorías temáticas y un mapa cartográfico. Se vio que las estrategias, consideradas líneas de fuga, permiten transformaciones en el trabajo en equipo, puesto que originan manantiales en suelos cristalizados, pensamientos problematizadores, subjetividad e interacciones disciplinarias. Se concluyó que las líneas duras no deben eliminarse del trabajo en equipo, puesto que coexisten en esta realidad y lo que importa es cómo se experimentan en las relaciones.

The study aimed to map the strategies used for collaborative work in Family Health Teams (FHT), inserted in Primary Health Care, in a municipality in the North of Minas. This is a qualitative study, with the methodological proposal of Cartography. Data were produced in four FHT, through participant observation, identification questionnaire, cartographic diary, semi-structured individual interview and focus group. Discourse analysis and mapping screening enabled the construction of two thematic categories and a cartographic map. It was reached that the strategies, considered lines of flight, allow existential transformations in teamwork, since they originate springs in crystallized soils, problematizing thoughts, subjectivity, and disciplinary interactions. It was concluded that hard lines should not be eliminated from teamwork, for they coexist in this reality, and what matters is how they are experienced in relationships.

Recovery Experience Questionnaire: validity evidence of the Brazilian-Portuguese version.

The aim is to present validity evidence of the Brazilian-Portuguese Recovery Experience Questionnaire (REQ-PB) by applying a procedure to decentering cross-cultural scales translation and adaptation. First, we had a phase with bilingual experts, which assessed different criteria of translation quality. In sequence, we conducted the replication of the original research to achieve validity indicators in the Brazilian context. We carried out both Confirmatory Factor Analysis (to find structural validity indicators) and correlations with various external variables (to find convergent validity indicators). Step 1 showed promising results of decentering translation. In step 2 participated 164 workers and the CFA confirmed the four-factor model: psychological detachment from work, relaxation, mastery experience, and control over leisure time. The convergent validity showed a significant correlation with external variables. The REQ-PB showed adequate psychometric properties and may explain and compare empirical evidence of the recovery topic. We concluded that we have a good quality scale to be used in future research and integrated with other constructs to support interventions.

Use of In silico Methodologies to Predict the Bioavailability of Oral Suspensions: A Regulatory Approach.

BACKGROUND: Oral suspensions are heterogeneous disperse systems, and the particle size distribution, crystalline form of the dispersed solid, and composition of the formulation can be listed as parameters that control the drug dissolution rate and its bioavailability. OBJECTIVE: The aim of this work was to develop a discriminative dissolution test, which, in association with in silico methodologies, can make it possible to safely anticipate bioavailability problems. METHODS: Nimesulide and ibuprofen (BCS class II) and cephalexin (BCS class I) oral suspensions were studied. Previously, solid-state structure and particle size in active pharmaceutical ingredients were characterized and the impact of differences on solubility was evaluated for the choice of discriminative medium. Afterwards, particle size distribution (0.1 to 360 µm), dissolution profile, and in vitro permeability in Caco-2 cell of commercial suspensions, were determined. These parameters were used as input for the establishment of the in vitro-in vivo correlation (IVIVC) for the suspensions using the GastroPlus™ with Wagner-Nelson and Loo- Riegelmann deconvolution approach. RESULTS: The predicted/observed pharmacokinetic model showed good correlation coefficients (r) of 0.960, 0.950, and 0.901, respectively. The IVIVC was established for one nimesulide and two ibuprofen suspensions with r between 0.956 and 0.932, and the percent prediction error (%PE) did not exceed 15%. CONCLUSION: In this work, we have performed a complete study combining in vitro/in silico approaches with the aim of anticipating the safety and efficacy of oral pharmaceutical suspensions in order to provide a regulatory tool for this category of products in a faster and more economical way.

Puerperal women's satisfaction with the obstetric services received: improvement of an assessment instrument.

OBJECTIVES: to improve an instrument that measures postpartum women's satisfaction with obstetric care. METHODS: action research, developed from a preliminary version of an instrument prepared by nurse-midwives working in public services in the Federal District. The analysis of the results of application of instrument carried out in a pilot test, analysis of evidence of instrument validity, literature review, focus group with the instrument's developers and interview with the target audience were carried out. RESULTS: factorial analysis showed three existing factors in the construct. Seven nurses participated, discussing the instrument reformulation, and 20 mothers reported their perceptions about the care received during childbirth, generating five thematic units. FINAL CONSIDERATIONS: instrument improvement occurred through item and response scale reconstruction and reorganization, in addition to application of a pre-test with the target population, resulting in an instrument composed of 13 items.

Recovery Experience Questionnaire: validity evidence of the Brazilian-Portuguese version / Questionário de Experiência de Restauro: evidências de validade da versão em português brasileiro

Abstract The aim is to present validity evidence of the Brazilian-Portuguese Recovery Experience Questionnaire (REQ-PB) by applying a procedure to decentering cross-cultural scales translation and adaptation. First, we had a phase with bilingual experts, which assessed different criteria of translation quality. In sequence, we conducted the replication of the original research to achieve validity indicators in the Brazilian context. We carried out both Confirmatory Factor Analysis (to find structural validity indicators) and correlations with various external variables (to find convergent validity indicators). Step 1 showed promising results of decentering translation. In step 2 participated 164 workers and the CFA confirmed the four-factor model: psychological detachment from work, relaxation, mastery experience, and control over leisure time. The convergent validity showed a significant correlation with external variables. The REQ-PB showed adequate psychometric properties and may explain and compare empirical evidence of the recovery topic. We concluded that we have a good quality scale to be used in future research and integrated with other constructs to support interventions.

Resumo O objetivo é apresentar evidências da validade do Questionário de Experiência de Restauro em português brasileiro (REQ-PB) por meio da aplicação de um procedimento de descentralização para tradução e adaptação de escalas transculturais. Inicialmente, tivemos uma fase com especialistas bilíngues que avaliaram a qualidade da tradução utilizando diferentes critérios. Na sequência, realizamos a replicação da pesquisa original para alcançar os indicadores de validade no contexto brasileiro. Efetuamos tanto a análise fatorial confirmatória (para encontrar indicadores de validade estrutural) quanto correlações com variáveis externas (para encontrar indicadores de validade convergentes). O passo 1 mostrou resultados promissores na tradução descentralizada. No passo 2, participaram 164 trabalhadores e a análise fatorial confirmatória confirmou o modelo de quatro fatores: distanciamento psicológico do trabalho, relaxamento, experiência de domínio e controle do tempo livre. A validade convergente mostrou uma correlação significativa com variáveis externas. O REQ-PB mostrou propriedades psicométricas adequadas capazes de explicar e comparar evidências empíricas do tópico de restauro. Em resumo, a escala pode ser utilizada em pesquisas futuras e integrada aoutros construtos para orientar intervenções.