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Callous unemotional (CU) traits refer to specific deficits in affective experience and interpersonal style, characterized by absence of guilt, constrictive display of emotion and failure to show empathy, callous use of others for one’s own gain. The Inventory of Callous-Unemotional Traits (ICU) was developed to measure CU traits in children and adolescents. The aim of this study was to analyze the factorial structure of the Portuguese version of teacher-report ICU for children in school age and examine psychometric properties such as internal consistency and convergent validity in a community sample. Thirty-six teachers provided behavioral ratings of 100 and 78 children of elementary school, 88 boys and 90 girls, aged between 6 and 10 years old. Confirmatory factor analyses provided further support to a 2-factor structure, comprising the following dimensions: callous and uncaring. This study showed that the ICU seems a reliable an accessible tool that can be used in the Portuguese educational context to evaluate CU traits with low time consumption.

Oxytocin (OT) is a key modulator of human social cognition, popular in behavioral neuroscience. To adequately design and interpret intranasal OT (IN-OT) research, it is crucial to know for how long it affects human brain function once administered. However, this has been mostly deduced from peripheral body fluids studies, or uncommonly used dosages. We aimed to characterize IN-OT’s effects on human brain function using resting-state EEG microstates across a typical experimental session duration. Nineteen healthy males participated in a double-blind, placebo-controlled, within-subject, cross-over design of 24 IU of IN-OT in 12-min windows 15 min-to-1 h 42min after administration. We observed IN-OT effects on all microstates, across the observation span. During eyes-closed, IN-OT increased duration and contribution of A and contribution and occurrence of D, decreased duration and contribution of B and C; and increased transition probability C-to-B and C-to-D. In eyes-open, it increased A-to-C and A-to-D. As microstates A and D have been related to phonological auditory and attentional networks, respectively, we posit IN-OT may tune the brain for reception of external stimuli, particularly of social nature—tentatively supporting current neurocognitive hypotheses of OT. Moreover, we contrast our overall results against a comprehensive literature review of IN-OT time-course effects in the brain, highlighting comparability issues.

Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is an age-related, epileptic syndrome, which associates cognitive/behavioral disturbances with a peculiar pattern of spike activity. One promising line of research is the study of ESES in cases of early thalamic lesions. We studied 7 ESES patients with unilateral thalamic lesions using magnetic resonance imaging to assess regional white matter (WM) and thalamic nuclei volume differences, and long-term electroencephalogram recordings to localize the epileptogenic cortex. N170 event-related potentials were used to demonstrate the dysfunctional character of the WM abnormalities. Diffusion-weighted images in a subset of 4 patients were used to parcellate the thalamus and evaluate volume asymmetries, based on cortical connectivity. Large WM regional atrophy in the hemisphere with the thalamic lesion was associated with both cortical dysfunction and epileptic activity. A correlation was demonstrated between lesions in the pulvinar and the mediodorsal thalamic nuclei and WM atrophy of the corresponding cortical projection areas. We propose that these abnormalities are due to the widespread structural disconnection produced by the thalamic lesions associated to a yet unknown age-dependent factor. Further exploration of WM regional atrophy association with the spike activity in other etiologies could lend support to the cortical disconnection role in ESES genesis. info:eu-repo/semantics/publishedVersion

Electroencephalogram microstates are recurrent scalp potential configurations that remain stable for around 90 ms. The dynamics of two of the four canonical classes of microstates, commonly labeled as C and D, have been suggested as a potential endophenotype for schizophrenia. For endophenotypes, unaffected relatives of patients must show abnormalities compared to controls. Here, we examined microstate dynamics in resting-state recordings of unaffected siblings of patients with schizophrenia, patients with schizophrenia, healthy controls, and patients with first episodes of psychosis (FEP). Patients with schizophrenia and their siblings showed increased presence of microstate class C and decreased presence of microstate class D compared to controls. No difference was found between FEP and chronic patients. Our findings suggest that the dynamics of microstate classes C and D are a candidate endophenotype for schizophrenia., EEG microstate abnormalities have been reported in patients with schizophrenia. Here the authors demonstrate that patients and their siblings show similar microstate abnormalities compared to healthy controls.

Introduction. Diabetic neuropathy (DN) is one of the most devastating complications of diabetes mellitus; however, in contrast to other countries, there are no scientific studies in Portugal evaluating the impact of demographic and clinical characteristics of this pathological entity. The aim of this study was to evaluate the impact of gender, metabolic control, age of diabetic patients, as well as time of disease progression, the appearance of complaints related to neuropathic pain. Material and methods. A multicentre study with a non-probabilistic, convenience sample of 359 patients was performed employing the quantitative method, using the Statistical Package for Social Science 24 software. The p-value of p < 0.05 was defined to consider a result statistically significant. The Spearman correlation coefficient (r) was determined to determine the relationship between categorical variables. Results. There was no statistically significant difference in the prevalence of DN between genders (p = 0.633 and r = 0.025). There was a statistically significant relationship between the value of HbA1c and DN, with p = 0.010 and r = 0.136. There is a relationship between age and complaints of neuropathic pain, with p = 0.034 and r = 0.112. The variable, time of disease progression, is also correlated with the appearance of complaints of neuropathic pain with p = 0.020 and r = 0.112. Conclusion. The prevalence of neuropathic pain in subjects with diabetes is not negligible and is associated with modifiable risk factors that can be identified, possibly modified and prevented. The correct approach for these patients, which involves screening and early treatment, is decisive improving functionality and quality of life.

Visual backward masking (VBM) deficits are candidate endophenotypes of schizophrenia indexing genetic liability of the disorder. In VBM, a target is followed by a mask that deteriorates target perception. Schizophrenia patients and, to a lesser extent, their unaffected relatives show strong and reproducible VBM deficits. In patients, VBM deficits are associated with strongly decreased amplitudes in the evoked-related potentials (ERPs). Here, to unveil the neural mechanisms of VBM in schizophrenia, circumventing illness-specific confounds, we investigated the electroencephalogram correlates of VBM in unaffected siblings of schizophrenia patients. We tested 110 schizophrenia patients, 60 siblings, and 83 healthy controls. As in previous studies, patients showed strong behavioral deficits and decreased ERP amplitudes compared to controls. Surprisingly, the ERP amplitudes of siblings were even higher than the ones of controls, while their performances were similar. ERP amplitudes in siblings were found to correlate with performance. These results suggest that VBM is deteriorated in patients and siblings. However, siblings, unlike patients, can partially compensate for the deficits by over-activating a network of brain regions.

Natural biopolymer nanoparticles (NPs), including nanocrystalline cellulose (CNC) and lignin, have shown potential as scaffolds for targeted drug delivery systems due to their wide availability, cost‐efficient preparation, and anticipated biocompatibility. Since both CNC and lignin can potentially cause complications in cell viability assays due to their ability to scatter the emitted light and absorb the assay reagents, we investigated the response of bioluminescent (CellTiter‐Glo®), colorimetric (MTT® and AlamarBlue®) and fluorometric (LIVE/DEAD®) assays for the determination of the biocompatibility of the multimodal CNC and lignin constructs in murine RAW 264.7 macrophages and 4T1 breast adenocarcinoma cell lines. Here, we have developed multimodal CNC and lignin NPs harboring the radiometal chelator DOTA (1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetraacetic acid) and the fluorescent dye Cyanine 5 for the investigation of nanomaterial biodistribution in vivo with nuclear and optical imaging, which were then used as the model CNC and lignin nanosystems in the cell viability assay comparison. CellTiter‐Glo® based on the detection of ATP‐dependent luminescence in viable cells revealed to be the best assay for both nanoconstructs for its robust linear response to increasing NP concentration and lack of interference from either of the NP types. Both multimodal CNC and lignin NPs displayed low cytotoxicity and favorable interactions with the cell lines, suggesting that they are good candidates for nanosystem development for targeted drug delivery in breast cancer and for theranostic applications. Our results provide useful guidance for cell viability assay compatibility for CNC and lignin NPs and facilitate the future translation of the materials for in vivo applications.

Social dominance, the main organizing principle of social hierarchies, facilitates priority access to resources by dominant individuals. Throughout taxa, individuals are more likely to become dominant if they act first in social situations and acting fast may provide evolutionary advantage; yet whether fast decision-making is a behavioral predisposition of dominant persons outside of social contexts is not known. Following characterization of participants for social dominance motivation, we found that, indeed, men high in social dominance respond faster–without loss of accuracy–than those low in dominance across a variety of decision-making tasks. Both groups did not differ in a simple reaction task. Then, we selected a decision-making task and applied high-density electroencephalography (EEG) to assess temporal dynamics of brain activation through event related potentials. We found that promptness to respond in the choice task in dominant individuals is related to a strikingly amplified brain signal at approximately 240 ms post-stimulus presentation. Source imaging analyses identified higher activity in the left insula and in the cingulate, right inferior temporal and right angular gyri in high than in low dominance participants. Our findings suggest that promptness to respond in choice situations, regardless of social context, is a biomarker for social disposition.

Nanomedicines represent innovative and promising alternative technologies to improve the therapeutic effects of different drugs for cancer ablation. Targeting M2-like tumor-associated macrophages (TAMs) has emerged as a favorable therapeutic approach to fight against cancer through the modulation of the tumor microenvironment. However, the immunomodulatory molecules used for this purpose present side effects upon systemic administration, which limits their clinical translation. Here, the biocompatible lignin polymer is used to prepare lignin nanoparticles (LNPs) that carry a dual agonist of the toll-like receptors TLR7/8 (resiquimod, R848). These LNPs are targeted to the CD206-positive M2-like TAMs using the “mUNO” peptide, in order to revert their pro-tumor phenotype into anti-tumor M1-like macrophages in the tumor microenvironment of an aggressive triple-negative in vivo model of breast cancer. Overall, we show that targeting the resiquimod (R848)-loaded LNPs to the M2-like macrophages, using very low doses of R848, induces a profound shift in the immune cells in the tumor microenvironment towards an anti-tumor immune state, by increasing the representation of M1-like macrophages, cytotoxic T cells, and activated dendritic cells. This effect consequently enhances the anticancer effect of the vinblastine (Vin) when co-administered with R848-loaded LNPs to the M2-like macrophages, using very low doses of R848, induces a profound shift in the immune cells in the tumor microenvironment towards an anti-tumor immune state, by increasing the representation of M1-like macrophages, cytotoxic T cells, and activated dendritic cells. This effect consequently enhances the anticancer effect of the vinblastine (Vin) when co-administered with R848-loaded LNPs. Statement of significance Lignin-based nanoparticles (LNPs) were successfully developed to target a potent TLR7/8 agonist (R848) of the tumor microenvironment (TME). This was achieved by targeting the mannose receptor (CD206) on the tumor supportive (M2-like) macrophages with the "mUNO" peptide, to reprogram them into an antitumor (M1-like) phenotype for enhanced chemotherapy. LNPs modified the biodistribution of the R848, and enhanced its accumulation and efficacy in shifting the immunological profile of the cells in the TME, which was not achieved by systemic administration of free R848. Moreover, a reduction in the tumor volumes was observed at lower equivalent doses of R848 compared with other studies. Therefore, the co-administration of R848@LNPs is a promising chemotherapeutic application in aggressive tumors, such as the triple-negative breast cancer. (c) 2020 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Objective: to discuss in the scientific literature the strategies used to prevent hypothermia in newborns undergoing surgical procedures. Methods this is an integrative literature review, with structured search in April and May 2020 in 08 databases, using the descriptors: Hypothermia; Surgical Procedures, Operative; Infant, Newborn; Protocols. Four primary studies were selected and analyzed using three instruments to assess the methodological quality of the Joanna Briggs Institute and content analysis. Results: Among the strategies used, the following stand out: room temperature control; establishment of humidification and quality of air conditioning cleanliness; use of a heated incubator or cradle; use of thermal mattress; use of caps and blanket; heated fluids; temperature monitoring and abdominal organ coverage. Conclusion good hypothermia prevention strategies were identified, despite the small number of publications on this topic; thus, it points out the need for research with strong evidence. RESUMEN Objetivo: discutir, en la literatura científica, las estrategias utilizadas para prevenir la hipotermia en recién nacidos sometidos a procedimientos quirúrgicos. Métodos: revisión integrativa de la literatura, con búsqueda estructurada en abril y mayo de 2020 en 08 bases de datos, utilizando los descriptores: Hypothermia; Surgical Procedures, Operative; Infant, Newborn; Protocols. Se seleccionaron y analizaron cuatro estudios primarios utilizando tres instrumentos para evaluar la calidad metodológica del Instituto Joanna Briggs y el análisis de contenido. Resultados: entre las estrategias empleadas destacan: control de la temperatura ambiente; establecimiento de humidificación y calidad de aire acondicionado limpio; uso de una incubadora o cuna con calefacción; uso de colchón térmico; uso de gorros y mantas; fluidos calentados; monitoreo de temperatura; cobertura de órganos abdominales. Conclusión: se identificaron buenas estrategias de prevención de la hipotermia, a pesar del escaso número de publicaciones sobre este tema; por lo tanto, señala la necesidad de realizar investigaciones con evidencia sólida. RESUMO Objetivo: discutir, na literatura científica, as estratégias utilizadas para prevenção de hipotermia em recém-nascido submetido a procedimentos cirúrgicos. Métodos: revisão integrativa de literatura, com busca estruturada em abril e maio de 2020 em 08 bases de dados, utilizando os descritores: Hypothermia; Surgical Procedures, Operative; Infant, Newborn; Protocols. Foram selecionados e analisados 04 estudos primários por meio de três instrumentos para avaliação da qualidade metodológica da Joanna Briggs Institute e da análise de conteúdo. Resultados: dentre as estratégias utilizadas destaca-se: controle da temperatura ambiente; estabelecimento de umidificação e qualidade de limpeza do ar condicionado; utilização de incubadora ou berço aquecido; uso de colchão térmico; uso de toucas e cobertor; fluidos aquecidos; monitoramento da temperatura; cobertura de órgãos abdominais. Conclusão: identificaram-se boas estratégias de prevenção de hipotermia, apesar de haver um número reduzido de publicações nesta temática; dessa forma, aponta-se a necessidade de pesquisas com evidências fortes.

© The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2022, Objective: Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small vessel disease (SVD), but methods and results have varied across studies. This work aims to assess the impact of mask selection for extracting histogram-based metrics of fractional anisotropy (FA) and mean diffusivity (MD) on their sensitivity as SVD biomarkers. Methods: DTI data were collected from 17 SVD patients and 12 healthy controls. FA and MD maps were estimated; from these, histograms were computed on two whole-brain white-matter masks: normal-appearing white-matter (NAWM) and mean FA tract skeleton (TBSS). Histogram-based metrics (median, peak height, peak width, peak value) were extracted from the FA and MD maps. These were compared between groups and correlated with the patients' cognitive scores (executive function and processing speed). Results: White-matter mask selection significantly impacted FA and MD histogram metrics. In particular, significant interactions were found between Mask and Group for FA peak height (p = 0.027), MD Median (p = 0.035) and MD peak width (p = 0.047); indicating that the mask used affected their ability to discriminate between groups. In fact, MD peak width showed a significant 8.8% increase in patients when using TBSS (p = 0.037), but not when using NAWM (p = 0.69). Moreover, the mask may have an effect on the correlations with cognitive measures. Nevertheless, MD peak width (TBSS: r = - 0.75, NAWM: r = - 0.71) and MD peak height (TBSS: r = 0.65, NAWM: r = 0.62) remained significantly correlated with executive function, regardless of the mask. Conclusion: The impact of the processing methodology, in particular the choice of white-matter mask, highlights the need for standardized MRI data-processing pipelines., We acknowledge the Portuguese Foundation for Science and Technology (FCT) for financial support through Grants SFRH/BD/139561/2018, PTDC/BBB-IMG/2137/2012, LISBOA-01-0145-FEDER-029675 and UIDB/50009/2020.

© 2021 AlphaMed Press., Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients with cancer show worse outcomes compared with patients without cancer. The humoral immune response (HIR) of patients with cancer against SARS-CoV-2 is not well characterized. To better understand it, we conducted a serological study of hospitalized patients with cancer infected with SARS-CoV-2. Materials and methods: This was a unicentric, retrospective study enrolling adult patients with SARS-CoV-2 admitted to a central hospital from March 15 to June 17, 2020, whose serum samples were quantified for anti-SARS-CoV-2 receptor-binding domain or spike protein IgM, IgG, and IgA antibodies. The aims of the study were to assess the HIR to SARS-CoV-2; correlate it with different cancer types, stages, and treatments; clarify the interplay between the HIR and clinical outcomes of patients with cancer; and compare the HIR of SARS-CoV-2-infected patients with and without cancer. Results: We included 72 SARS-CoV-2-positive subjects (19 with cancer, 53 controls). About 90% of controls revealed a robust serological response. Among patients with cancer, a strong response was verified in 57.9%, with 42.1% showing a persistently weak response. Treatment with chemotherapy within 14 days before positivity was the only factor statistically shown to be associated with persistently weak serological responses among patients with cancer. No significant differences in outcomes were observed between patients with strong and weak responses. All IgG, IgM, IgA, and total Ig antibody titers were significantly lower in patients with cancer compared with those without. Conclusion: A significant portion of patients with cancer develop a proper HIR. Recent chemotherapy treatment may be associated with weak serological responses among patients with cancer. Patients with cancer have a weaker SARS-CoV-2 antibody response compared with those without cancer. Implications for practice: These results place the spotlight on patients with cancer, particularly those actively treated with chemotherapy. These patients may potentially be more vulnerable to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, so it is important to provide oncologists further theoretical support (with concrete examples and respective mechanistic correlations) for the decision of starting, maintaining, or stopping antineoplastic treatments (particularly chemotherapy) not only on noninfected but also on infected patients with cancer in accordance with cancer type, stage and prognosis, treatment agents, treatment setting, and SARS-CoV-2 infection risks., LtoINNOV), the Fundação para a Ciência e a Tecnologia (SFRH/BD/131605/2017), and research4COVID19 (231_596873172, generating SARS-CoV-2 seroconversion assay), with additional support by Sociedade Francisco Manuel dos Santos.

Polyoxometalates are an emerging class of molecular clusters, with well-defined structures and chemical compositions that are produced through simple, low-cost, and highly reproducible methods. In particular, the wheel-shaped cluster {Mo

© 2020 The Authors. European Journal of Immunology published by Wiley‐VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., SARS-CoV-2 has emerged as a human pathogen, causing clinical signs, from fever to pneumonia-COVID-19-but may remain mild or asymptomatic. To understand the continuing spread of the virus, to detect those who are and were infected, and to follow the immune response longitudinally, reliable and robust assays for SARS-CoV-2 detection and immunological monitoring are needed. We quantified IgM, IgG, and IgA antibodies recognizing the SARS-CoV-2 receptor-binding domain (RBD) or the Spike (S) protein over a period of 6 months following COVID-19 onset. We report the detailed setup to monitor the humoral immune response from over 300 COVID-19 hospital patients and healthcare workers, 2500 University staff, and 198 post-COVID-19 volunteers. Anti-SARS-CoV-2 antibody responses follow a classic pattern with a rapid increase within the first three weeks after symptoms. Although titres reduce subsequently, the ability to detect anti-SARS-CoV-2 IgG antibodies remained robust with confirmed neutralization activity for up to 6 months in a large proportion of previously virus-positive screened subjects. Our work provides detailed information for the assays used, facilitating further and longitudinal analysis of protective immunity to SARS-CoV-2. Importantly, it highlights a continued level of circulating neutralising antibodies in most people with confirmed SARS-CoV-2., We like to acknowledge the funding from the European Union H2020 ERA project (No 667824 – EXCELLtoINNOV) and the Fundação para a Ciência e a Tecnologia (FCT) to P.F‐C. (SFRH/BD/131605/2017), PTDC/MED‐IMU/28003/2017, and research4COVID19 (no. 231_596873172, Generating SARS‐CoV2 seroconversion assay and no. 729, High‐throughput SARS‐CoV2 neutralizing antibodies assessment), with additional support by Sociedade Francisco Manuel dos Santos.

BackgroundMining activities have environmental impacts due to sediment movement and contamination of areas and may also pose risks to people’s food security. In Brazil, the majority of coal mining activities are in the south, in the Santa Catarina carboniferous region. In this region, previously mined areas contaminated with heavy metals frequently occur nearby inhabited zones. Mining is part of the daily lives of local communities, and its environmental impacts are visible in the landscape; however, plants with medicinal and food use from these areas can be still consumed. Heavy metals are contaminants that do not have odor, color, or taste, and are therefore difficult to detect. We aimed to verify whether people use plants from contaminated mine areas, and understand which factors can influence the use of these resources, even from areas visibly impacted.MethodsWe conducted 195 semi-structured interviews with residents from 14 areas nearby abandoned mines in the main municipalities of the Santa Catarina carboniferous region. We asked each interviewee about the length of time they lived in the region, their perception of the quality of the environment, and what plant species were used and for what purpose. We constructed generalized multivariate linear models to verify which variables can affect the group of species mentioned and generalized linear models to verify which variables can affect the total number of citations. We estimated the frequency of citing species collected using the Smith index.ResultsFrom all interviewees, 127 (65%) reported collecting plants for medicinal and food use, directly from contaminated mine areas. Long-term residents, as well as those who noticed more environmental changes (positive and negative), cited more plants used and had more detailed knowledge of plant use in their communities. When asked if they were aware of the possible contamination of mined areas, 85% said they knew about it. However, only 10% associated negative health effects with the use of plant species collected in contaminated mined areas.ConclusionsOur study demonstrates that people living nearby contaminated areas use and consume locally sourced plants, e.g., people know little about the danger of this contamination in their food and the risk of these contaminants to their health. These results also reveal a lack of information about contamination, as well as a lack of actions that include local communities in contaminated area restoration strategies. This situation poses a risk to the food security of the people living nearby former coal mining areas.

UIDB/50006/2020 PD/BD/142880/2018 UID/DTP/04138/2020 Here, a continuous two-step glass-capillary microfluidic technique to produce a multistage oral delivery system is reported. Insulin is successfully encapsulated into liposomes, which are coated with chitosan to improve their mucoadhesion. The encapsulation in an enteric polymer offers protection from the harsh gastric conditions. Insulin permeability is enhanced across an intestinal monolayer. publishersversion published

Brain functional connectivity measured by resting-state fMRI varies over multiple time scales, and recurrent dynamic functional connectivity (dFC) states have been identified. These have been found to be associated with different cognitive and pathological states, with potential as disease biomarkers, but their neuronal underpinnings remain a matter of debate. A number of recurrent microstates have also been identified in resting-state EEG studies, which are thought to represent the quasi-simultaneous activity of large-scale functional networks reflecting time-varying brain states. Here, we hypothesized that fMRI-derived dFC states may be associated with these EEG microstates. To test this hypothesis, we quantitatively assessed the ability of EEG microstates to predict concurrent fMRI dFC states in simultaneous EEG-fMRI data collected from healthy subjects at rest. By training a random forests classifier, we found that the four canonical EEG microstates predicted fMRI dFC states with an accuracy of 90%, clearly outperforming alternative EEG features such as spectral power. Our results indicate that EEG microstates analysis yields robust signatures of fMRI dFC states, providing evidence of the electrophysiological underpinnings of dFC while also further supporting that EEG microstates reflect the dynamics of large-scale brain networks.

Delinquent behavior describes one of the most severe forms of antisocial and aggressive behavior, causing the highest mental health and public expenditures of problematic behavior in adolescence. Literature suggests that different concentrations of cortisol may serve as a biological marker for a severe antisocial subgroup of adolescents, although from the environmental risk factors that play a role in the development of severe delinquent and aggressive behavior, other neurobiological factors may be important. This review aims to analyze the association of cortisol levels with the development of delinquent behavior. Studies related to the topic were obtained from multiple databases, through rigorous exclusion and inclusion criteria. Only papers with empirical and quantitative methodologies from scientific and academic publications were included. Aims, methodological aspects (sample and instruments), and main conclusions were extracted from each study. Overall, the data suggest that regardless of the literature relating low cortisol levels to conduct problems and antisocial behavior, the lack of consensus in the examined studies demonstrates that more studies are needed to reveal the role of biosocial mechanisms in this hormonal-behavior link, and how these mechanisms are involved in establishing and maintaining delinquent behavior.

The advent of nanomedicine has recently started to innovate the treatment of cardiovascular diseases, in particular myocardial infarction. Although current approaches are very promising, there is still an urgent need for advanced targeting strategies. In this work, the exploitation of macrophage recruitment is proposed as a novel and synergistic approach to improve the addressability of the infarcted myocardium achieved by current peptide-based heart targeting strategies. For this purpose, an acetalated dextran-based nanosystem is designed and successfully functionalized with two different peptides, atrial natriuretic peptide (ANP) and linTT1, which target, respectively, cardiac cells and macrophages associated with atherosclerotic plaques. The biocompatibility of the nanocarrier is screened on both macrophage cell lines and primary macrophages, showing high safety, in particular after functionalization of the nanoparticles' surface. Furthermore, the system shows higher association versus uptake ratio towards M2-like macrophages (approximately 2-fold and 6-fold increase in murine and human primary M2-like macrophages, respectively, compared to M1-like). Overall, the results demonstrate that the nanosystem has potential to exploit the "hitchhike" effect on M2-like macrophages and potentially improve, in a dual targeting strategy, the ability of the ANP peptide to target infarcted heart.

Objective With the advent of high-density EEG and studies of large numbers of participants, yielding increasingly greater amounts of data, supervised methods for artifact rejection have become excessively time consuming. Here, we propose a novel automatic pipeline (APP) for pre-processing and artifact rejection of EEG data, which innovates relative to existing methods by not only following state-of-the-art guidelines but also further employing robust statistics. Methods APP was tested on event-related potential (ERP) data from healthy participants and schizophrenia patients, and resting-state (RS) data from healthy participants. Its performance was compared with that of existing automatic methods (FASTER for ERP data, TAPEEG and Prep pipeline for RS data) and supervised pre-processing by experts. Results APP rejected fewer bad channels and bad epochs than the other methods. In the ERP study, it produced significantly higher amplitudes than FASTER, which were consistent with the supervised scheme. In the RS study, it produced spectral measures that correlated well with the automatic alternatives and the supervised scheme. Conclusion APP effectively removed EEG artifacts, performing similarly to the supervised scheme and outperforming existing automatic alternatives. Significance The proposed automatic pipeline provides a reliable and efficient tool for pre-processing large datasets of both evoked and resting-state EEG.

External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI.

Currently, nanosystems have been developed and applied as promising vehicles for different biomedical applications. We have developed three lignin nanoparticles (LNPs): pure lignin nanoparticles (pLNPs), iron(III)-complexed lignin nanoparticles (Fe-LNPs), and Fe3O4-infused lignin nanoparticles (Fe3O4-LNPs) with round shape, narrow size distribution, reduced polydispersity and good stability at pH 7.4. The LNPs showed low cytotoxicity in all the tested cell lines and hemolytic rates below 12% after 12 h of incubation. Additionally, they induced hydrogen peroxide production in a small extent and time-dependent manner, and the interaction with the cells increased over time, exhibiting a dose-dependent cell uptake. Concerning the drug loading, pLNPs showed the capacity to efficiently load poorly water-soluble drugs and other cytotoxic agents, e.g. sorafenib and benzazulene (BZL), and improve their release profiles at pH 5.5 and 7.4 in a sustained manner. Furthermore, the BZL-pLNPs presented an enhanced antiproliferation effect in different cells compared to the pure BZL and showed a maximal inhibitory concentration ranging from 0.64 to 12.4 μM after 24 h incubation. Overall, LNPs are promising candidates for drug delivery applications, and the superparamagnetic behavior of Fe3O4-LNPs makes them promising for cancer therapy and diagnosis, such as magnetic targeting and magnetic resonance imaging.

Tissue-resident memory T (T

Electroencephalography (EEG) neurofeedback (NF) training has been shown to produce long-lasting effects on the improvement of cognitive function as well as the normalization of aberrant brain activity in disease. However, the impact of the sensory modality used as the NF reinforcement signal on training effectiveness has not been systematically investigated. In this work, an EEG-based NF-training system was developed targeting the individual upper-alpha (UA) band and using either a visual or an auditory reinforcement signal, so as to compare the effects of the two sensory modalities. Sixteen healthy volunteers were randomly assigned to the Visual or Auditory group, where a radius-varying sphere or a volume-varying sound, respectively, reflected the relative amplitude of UA measured at EEG electrode Cz. Each participant underwent a total of four NF sessions, of approximately 40 min each, on consecutive days. Both groups showed significant increases in UA at Cz within sessions, and also across sessions. Effects subsequent to NF training were also found beyond the target frequency UA and scalp location Cz, namely in the lower-alpha and theta bands and in posterior brain regions, respectively. Only small differences were found on the EEG between the Visual and Auditory groups, suggesting that auditory reinforcement signals may be as effective as the more commonly used visual signals. The use of auditory NF may potentiate training protocols conducted under mobile conditions, which are now possible due to the increasing availability of wireless EEG systems.

Over the last decade, we have witnessed consistent advances in risk assessment procedures, namely the validation of those used with juveniles who have committed sexual offenses. The adaptation of these instruments into other languages requires research examining the conceptual and metric equivalence of the instruments, not just translation equivalence. Informed by data from 141 boys, aged 13 to 18, the psychometric properties of the Portuguese version of the Juvenile Sex Offender Assessment Protocol–II (J-SOAP-II), regarding reliability and construct validation, are presented and discussed. Factor structure, internal consistency, and interrater reliability were examined, and a reliable factorial structure that was consistent with the original validation of the J-SOAP was found. Scales 2 and 3 had good internal consistency, and Scale 1 had acceptable internal consistency. Results regarding concurrent validity revealed mostly statistically significant correlations. The implications of this research for juvenile sex offender risk assessments are discussed., The author(s) received no financial support for the research, authorship, and/or publication of this article.

The surface modification of nanoparticles (NPs) using different ligands is a common strategy to increase NP−cell interactions. Here, dentin phosphophoryn‐derived peptide (DSS) lignin nanoparticles (LNPs) are prepared and characterized, the cellular internalization of the DSS‐functionalized LNPs (LNPs‐DSS) into three different cancer cell lines is evaluated, and their efficacy with the widely used iRGD peptide is compared. It is shown that controlled extent of carboxylation of lignin improves the stability at physiological conditions of LNPs formed upon solvent exchange. Functionalization with DSS and iRGD peptides maintains the spherical morphology and moderate polydispersity of LNPs. The LNPs exhibit good cytocompatibility when cultured with PC3‐MM2, MDA‐MB‐231, and A549 in the conventional 2D model and in the 3D cell spheroid morphology. Importantly, the 3D cell models reveal augmented internalization of peptide‐functionalized LNPs and improve antiproliferative effects when the LNPs are loaded with a cytotoxic compound. Overall, LNPs‐DSS show equal or even superior cellular internalization than the LNPs‐iRGD, suggesting that DSS can also be used to enhance the cellular uptake of NPs into different types of cells, and release different cargos intracellularly.

Delinquency refers to a juveniles' behavior pattern characterized by repeated offending, and is regarded mainly in its social, but also criminal aspects. Delinquent and non-delinquent individuals may be a product of the same society or even the same family. Young individuals who are unable to find affection and protection within the family may become more susceptible to delinquency as a form of empowerment. More than socioeconomic conditions, the lack of interaction between parents and children, the existence of psychopathological problems in either parent, and academic problems, together with a biological vulnerability, may be deciding factors for the involvement of young individuals in delinquent behavior. This review aims to analyze the influence of environmental and genetic factors in the development of delinquent behavior. Studies related to the influence of the environment and genes on the development of delinquent behavior were obtained from multiple databases, through rigorous exclusion and inclusion criteria. Of the 152 documents retrieved, 87 were retained for further analysis, and 36 final studies were considered eligible for inclusion. In addition to these, ten studies were added trough manual search, with the final sample thus comprising 46 articles, published between 1983 and 2016. Objectives, methodological aspects (samples and instruments), and main conclusions were extracted from each study. Overall, the interaction between genetic and environmental factors appears to best explain the variation of delinquent behavior. Environmental risk factors may have differential effects on the behavior of individuals, particularly according to their genetic propensity for delinquency.

Breast cancer, with around 2 million new cases in 2019, is the second most common cancer worldwide and the second leading cause of cancer death among females. The aim of this work is to prepare a targeting nanoparticle through the conjugation of LinTT1 peptide, a specific molecule targeting p32 protein overexpressed by breast cancer and cancer associated cells, on liposomes' surface. This approach increases the cytotoxic effects of doxorubicin (DOX) and sorafenib (SRF) co-loaded in therapeutic liposomes on both 2D and 3D breast cancer cellular models. The liposome functionalization leads to a higher interaction with 3D breast cancer spheroids than bare ones. Moreover, interaction studies between LinTT1-functionalized liposomes and M2 primary human macrophages show an internalization of 50% of the total nanovesicles that interact with these cells, while the other 50% results only associated to cell surface. This finding suggests the possibility to use the amount of associated liposomes to enrich the hypoxic tumor area, exploiting the ability of M2 macrophages to accumulate in the central core of tumor mass. These promising results highlight the potential use of DOX and SRF co-loaded LinTT1-functionalized liposomes as nanomedicines for the treatment of breast cancer, especially in triple negative cancer cells.

A targeted drug delivery nanosystem for glioblastoma multiforme (GBM) based on polymersomes (Ps) made of poly(dimethylsiloxane)-poly(2-methyloxazoline) (PDMS-PMOXA) diblock copolymers was developed to evaluate their potential to actively target brain cancer cells and deliver anticancer drugs. Angiopep2 was conjugated to the surface of preformed Ps to target the low density lipoprotein receptor-related protein 1 that are overexpressed in blood brain barrier (BBB) and glioma cells. The conjugation efficiency yield for angiopep2 was estimated to be 24%. The angiopep2-functionalized Ps showed no cellular toxicity after 24h and enhanced the cellular uptake around 5 times more in U87MG glioblastoma cells compared to the non-targeted Ps. The encapsulation efficiency of doxorubicin (DOX) in Ps was 13% by co-solvent method, compared to a film rehydration method (4%). The release profiles of the DOX from Ps showed a release of 42% at pH 5.5 and 40% at pH 7.4 after 24h, indicating that Ps can efficiently retain the DOX with a slow release rate. Furthermore, the in vitro antiproliferative activity of DOX-loaded Ps-Angiopep2 showed enhanced toxicity to U87MG glioblastoma cells, compared to non-targeted Ps. Overall, our in vitro results suggested that angiopep2-conjugated Ps can be used as nanocarriers for efficient targeted DOX delivery to glioblastoma cells.

Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD-fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter.

Purpose To verify sociodemographic factors associated with the occurrence of abortion in women of reproductive age, in areas covered by the Family Health Strategy (FHS), a program from the Brazilian Ministry of Health. Methods A cross-sectional study using household surveys of 350 women aged 15 to 49. The report of abortion was a variable indicator, and sociodemographic aspects were covariables. Prevalence ratio (PR) and respective 95% confidence intervals were used to estimate the magnitude of the associations. Results There were associations among age, civil status, race/color, and religion; an increase in the prevalence of lower levels of education, age less than 20, and student status were protective factors. Conclusion The association between sociodemographic characteristics and the report of abortion is attributed to the fact that there is a lack at the FHS in the availability of fundamental healthcare services for young women; these findings call for action to guarantee the access to information about contraceptives and guidance to decrease the risk of unplanned pregnancies and abortions. Resumo Objetivo Verificar fatores sociodemográficos associados à ocorrência de aborto em mulheres em idade reprodutiva, em área de cobertura de Estratégia Saúde da Família ( ESF ). Métodos Estudo de corte transversal, por inquérito domiciliar com 350 mulheres de 15 a 49 anos de idade. Relato de aborto constituiu variável indicadora e aspectos sociodemográficos covariáveis. Utilizou-se a razão de prevalência (RP) e respectivos intervalos de confiança a 95% para estimar a magnitude das associações. Resultados Houve associação entre idade, estado civil, raça/cor e religião. Aumento da prevalência na menor escolaridade e ser menor de 20 anos e estudante constituíram fator de proteção. Conclusão A associação entre características sociodemográficas e relato de aborto remete a uma atenção à saúde na ESF sem cumprimento dos fundamentos das políticas para mulheres, e suscita ações que garantam às jovens acesso a informações, contraceptivos e a orientações que diminuam os riscos de gravidez não planejada e de abortos.

Background Independent Component Analysis (ICA) is commonly used for the identification of sources of interest in electroencephalographic (EEG) data, but the selection of the relevant components remains an open issue depending on the specific application. New Method We propose a novel approach for the objective selection of epilepsy-related independent components (ICs) from EEG data collected during functional Magnetic Resonance Imaging (fMRI) acquisitions, called PROJection onto Independent Components (PROJIC). Inter-ictal epileptiform discharges (IEDs) are identified on a reference EEG dataset collected outside the MRI scanner by an expert neurophysiologist, and the resulting average IED is projected onto the IC space of the EEG data collected simultaneously with fMRI. The power of the IED projection is then used to inform a k-means clustering algorithm of the ICs, allowing for the classification of epilepsy-related ICs. Comparison with existing methods The performance of PROJIC was compared with two methods previously proposed for the objective selection of EEG ICs of interest, which are based on the explicit similarity of the ICs with spatio-temporal templates of the events of interest, instead of the projection power. Results The proposed PROJIC method outperformed the others for both artificial and real data (19 datasets collected from 6 patients with drug-refractory focal epilepsy), with an average accuracy of 98.6%. Conclusions The ability of our method to accurately and objectively select epilepsy-related ICs makes it an important contribution for simultaneous EEG–fMRI epilepsy studies, with potential applications in the analysis of event-related EEG activity more generally, and also in EEG artefact correction.

REVIEW QUESTION/OBJECTIVE The objective of this review is to synthesize qualitative evidence on the experiences of women undergoing an induced abortion resulting from an unplanned pregnancy.More specifically, the review question is: how do women experience induced abortions resulting from an unplanned pregnancy?

Depression and schizophrenia are two psychiatric diseases with high co-morbidity. For this reason, it is important to find sensitive endophenotypes, which may disentangle the two disorders. The Shine-Through paradigm, a visual backward masking task, is a potential endophenotype for schizophrenia. Masking is strongly deteriorated in schizophrenia patients, which is reflected in reduced EEG amplitudes. Here, we tested whether masking deficits and associated EEG changes are also found in patients with major depressive disorder. First, we replicated previous findings showing that depressive patients exhibit, at most, only weak masking deficits. Second, we found that the EEG amplitudes of depressive patients were reduced compared to controls and slightly increased compared to schizophrenia patients. As a secondary analysis, we compared the performance in the masking paradigm with three cognitive tasks, namely: the Wisconsin card sorting test, a verbal fluency test and a degraded continuous performance test. Performance in all but the verbal fluency test could discriminate schizophrenia from depression.

The aim of the present study was to prepare niosome formulations for the simultaneous encapsulation, dual drug therapy, of two anticancer drugs by the ecological probe sonication method. Poloxamer and sorbitan monostearate were used as surface active agents in niosomes, and the water soluble doxorubicin and poorly-water soluble paclitaxel were used as anticancer drugs. Thorough physicochemical analysis were performed for the niosomes, and their cytotoxicity and activity were evaluated on MCF-7 and PC3-MM2 cancer cell lines. Prepared niosomes were small in size with sizes ranging from 137 nm to 893 nm, and entrapment efficiencies were high, ranging from 91.24% to 99.99%. During the four weeks stability testing, the particle size remained stable. The niosomal formulations showed in vitro sustained drug release profiles for doxorubicin and clearly increased the dissolution rate of poorly water soluble paclitaxel. The incorporation of both the drugs into niosomes improved cell penetration and antiproliferative activity of the drugs PC3-MM2 cell lines. As a conclusion, doxorubicin and paclitaxel loaded niosome formulations resulted in relatively stable, small sized niosomes with improved drug release profiles, low toxicity, better cell penetration and antiproliferative activity. The niosomes showed synergistic effect due to the presence of both drugs, which can overcome multidrug resistance.

The use of drug nanocrystals in the drug formulation is increasing due to the large number of poorly water-soluble drug compounds synthetized and due to the advantages brought by the nanonization process. The downsizing processes are done using a top-down approach (milling and homogenization currently employed at the industrial level), while the crystallization process is performed by bottom-up techniques (e.g., antisolvent precipitation, use of supercritical fluids or spray and freeze drying). In addition, the production of nanocrystals in confined environment can be achieved within microfluidics channels. This review analyzes the processes for the preparation of nanocrystals and co-crystals, divided by top-down and bottom-up approaches, together with their combinations. The combination of both strategies merges the favorable features of each process and avoids the disadvantages of single processes. Overall, the applicability of drug nanocrystals is highlighted by the widespread research on the production processes at the engineering, pharmaceutical, and nanotechnology level.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7 T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Neural Signals and Images”.Background: Dynamic Causal Modelling (DCM) is a generic formalism to study effective brain connectivity based on neuroimaging data, particularly functional Magnetic Resonance Imaging (fMRI). Recently, there have been attempts at modifying this model to allow for stochastic disturbances in the states of the model.Objectives: This paper proposes the Multiple- Model Kalman Filtering (MMKF) technique as a stochastic identification model discriminating among different hypothetical connectivity structures in the DCM framework; moreover, the performance compared to a similar de terministic identification model is assessed.Methods: The integration of the stochastic DCM equations is first presented, and a MMKF algorithm is then developed to perform model selection based on these equations. Monte Carlo simulations are performed in order to investigate the ability of MMKF to distinguish between different connectivity structures and to estimate hidden states under both deterministic and stochastic DCM.Results: The simulations show that the proposed MMKF algorithm was able to successfully select the correct connectivity model structure from a set of pre-specified plausible alternatives. Moreover, the stochastic approach by MMKF was more effective compared to its deterministic counterpart, both in the selection of the correct connectivity structure and in the estimation of the hidden states.Conclusions: These results demonstrate the applicability of a MMKF approach to the study of effective brain connectivity using DCM, particularly when a stochastic formulation is desirable.

Aim: To carboxylate kraft lignin toward the functionalization of carboxylated lignin nanoparticles (CLNPs) with a block copolymer made of PEG, poly(histidine) and a cell-penetrating peptide and then evaluate the chemotherapeutic potential of the innovative nanoparticles. Materials & methods: The produced nanoparticles were characterized and evaluated in vitro for stability and biocompatibility and the drug release profiles and antiproliferative effect were also assessed. Results: The prepared CLNPs showed spherical shape and good size distribution, good stability in physiological media and low cytotoxicity in all the tested cell lines. A poorly water-soluble cytotoxic agent was successfully loaded into the CLNPs, improving its release profiles in a pH-sensitive manner and showing an enhanced antiproliferative effect in the different cancer cells compared with a normal endothelial cell line. Conclusion: The resulting CLNPs are promising candidates for anticancer therapy.

Objective We hypothesize that the hypersynchronization associated with epileptic activity is best described by EEG synchronization measures, and propose to use these as predictors of epilepsy-related BOLD fluctuations. Methods We computed the phase synchronization index (PSI) and global field synchronization (GFS), within two frequency bands, a broadband (1–45 Hz) and a narrower band focused on the presence of epileptic activity (3–10 Hz). The associated epileptic networks were compared with those obtained using conventional unitary regressors and two power-weighted metrics (total power and root mean square frequency), on nine simultaneous EEG-fMRI datasets from four epilepsy patients, exhibiting inter-ictal epileptiform discharges (IEDs). Results The average PSI within 3–10 Hz achieved the best performance across several measures reflecting reliability in all datasets. The results were cross-validated through electrical source imaging of the IEDs. The applicability of PSI when no IEDs are recorded on the EEG was evaluated on three additional patients, yielding partially plausible networks in all cases. Conclusions Epileptic networks can be mapped based on the EEG PSI metric within an IED-specific frequency band, performing better than commonly used EEG metrics. Significance This is the first study to investigate EEG synchronization measures as potential predictors of epilepsy-related BOLD fluctuations.

Ethionamide (ETH) is an important second-line antituberculosis drug used for the treatment of patients infected with multidrug-resistant Mycobacterium tuberculosis. Recently, we reported that the loading of ETH into thermally carbonized-porous silicon (TCPSi) nanoparticles enhanced the solubility and permeability of ETH at different pH-values and also increased its metabolization process. Based on these results, we synthesized carboxylic acid functionalized thermally hydrocarbonized porous silicon nanoparticles (UnTHCPSi NPs) conjugated with ETH and its antimicrobial effect was evaluated against Mycobacterium tuberculosis strain H37Rv. The activity of the conjugate was increased when compared to free-ETH, which suggests that the nature of the synergy between the NPs and ETH is likely due to the weakening of the bacterial cell wall that improves conjugate-penetration. These ETH-conjugated NPs have great potential in reducing dosing frequency of ETH in the treatment of multidrug-resistant tuberculosis (MDR-TB). (C) 2016 Elsevier Ltd. All rights reserved., Fundação para a Ciência e Tecnologia (FCT, Portugal) and FEDER (European Union) for funding through UID/MULTI/04378/2013, project grant IF/00092/2014 and IF2014 position. Thanks are also due to “Comissão de Coordenação e Desenvolvimento Regional do Norte (CCDR-N)/NORTE2020/Portugal 2020” for funding through project DESignBIOtechHealth (ref. Norte-01-0145-FEDER-000024). H.A.S. acknowledges financial support from the Academy of Finland (decision nos. 252215 and 281300), the University of Helsinki Research Funds, the Biocentrum Helsinki, and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013, Grant No. 310892). The content is solely the responsibility of the authors and does not necessarily represent the official views of the FCT or CCDR-N, info:eu-repo/semantics/publishedVersion

Congestive heart failure (CHF) occurs when the heart can no longer maintain the baseline metabolic demand triggered by physiological venous pressure. In the pediatric population, it corresponds to a complex entity with multiple etiologies, depending on the age group assessed, being mainly associated with congenital structural malformations, cardiomyopathies, or secondary to arrhythmogenic, infectious, ischemic, toxic or infiltrative events1. The incidence of CHF in children also varies according to the underlying condition, ranging from 15% to 25% in patients with congenital heart defects. In structurally normal hearts, cardiomyopathy is the major factor associated with CHF, with a 40% incidence of CHF reported in those patients1. Isolated noncompaction cardiomyopathy is a rare disease, whose incidence in the general population ranges from 0.014% to 1.3%. It might result from a failure in compaction of the ventricular myocardium between weeks 5 and 8 of the embryonic life, leading to the persistence of myocardial trabeculations and deep recesses, which communicate with the ventricular cavity, generating myocardial thickening in two distinct layers (compacted and noncompacted). Initially reported in the pediatric population or with a congenital cardiopathy, it also affects adults with no other heart disease2,3. This failure in the regression of embryonic sinusoids is postulated to be due to the extremely high pressures that the ventricles undergo in that developmental period. However, the literature has reported a genetic aspect emphasizing the relationship of the disease with different genes, such as the mutation of gene G4.5 in families with severe infantile noncompaction cardiomyopathy, mutations P121L, CYPHER/ZASP, E101K, and a locus containing the disease gene in chromosome 11p153. The major complications of patients with noncompaction cardiomyopathy are pulmonary thromboembolism, arrhythmias and CHF3. In addition to the usual treatment of CHF, new classes of drugs, such as the phosphodiesterase type 5 (PDE-5) inhibitors, have been studied4. They are currently used for the treatment of erectile dysfunction and pulmonary arterial hypertension, and began to be studied for the treatment of CHF after the demonstration of higher PDE-5 expression in myocytes and vascular muscle cells, as well as of markers of oxidative stress in patients with CHF5. We report, for the first time, the clinical and laboratory findings of a patient with noncompaction cardiomyopathy after the addition of sildenafil (PDE-5 inhibitor) to the usual treatment.

Segmented three-dimensional echo planar imaging (3D-EPI) provides higher image signal-to-noise ratio (SNR) than standard single-shot two-dimensional echo planar imaging (2D-EPI), but is more sensitive to physiological noise. The aim of this study was to compare physiological noise removal efficiency in single-shot 2D-EPI and segmented 3D-EPI acquired at 7 Tesla. Two approaches were investigated based either on physiological regressors (PR) derived from cardiac and respiratory phases, or on principal component analysis (PCA) using additional resting-state data. Results show that, prior to physiological noise removal, 2D-EPI data had higher temporal SNR (tSNR), while spatial SNR was higher in 3D-EPI. Blood oxygen level dependent (BOLD) sensitivity was similar for both methods. The PR-based approach allowed characterization of relative contributions from different noise sources, confirming significant increases in physiological noise from 2D to 3D prior to correction. Both physiological noise removal approaches produced significant increases in tSNR and BOLD sensitivity, and these increases were larger for 3D-EPI, resulting in higher BOLD sensitivity in the 3D-EPI than in the 2D-EPI data. The PCA-based approach was the most effective correction method, yielding higher tSNR values for 3D-EPI than for 2D-EPI postcorrection.

Dyslipidemia is one of the main risk factors associated with cardiovascular diseases. Few data on the impacts of congenital heart diseases are available with regard to the prevalence of dyslipidemia in children. Our study evaluated the lipid profile in children with congenital heart disease at a referral center. From January 2011 to July 2012, 52 pediatric patients had their lipid, metabolic and clinical profiles traced. The mean age was 10.4 ± 2.8 years and male/female rate of 1.38:1. Our population had 53.8% patients with high levels of total cholesterol and 13.4% (CI 95 %, from 6.6 to 25.2%) of them also presenting LDL levels ≥ 130 mg/dL, which characterizes dyslipidemia. The group of dyslipidemic patients presented only two obese individuals. Our data show that the presence of congenital heart disease does not lead to higher risk associated with the prevalence of dyslipidemia. Therefore, the screening of this specific population should follow the regular pediatric guidelines, which are also independent of the nutritional status of the children tested.

Purpose To study arterial spin labeling (ASL) MRI techniques and to investigate various problematic issues that still hinder the accurate and robust quantitative analysis of ASL data. Materials and Methods A pulsed-ASL (PASL) sequence was implemented on a 3-T imaging system and a protocol was developed for the measurement of perfusion based on fitting to a standard kinetic model. Both numerical simulations and multi-inversion time MRI data were analyzed. The effect of fitting a kinetic curve to a large region of interest (ROI) with a distribution of arterial transit times was compared to a pixel-by-pixel (PBP) method. Results It was found that a significant underestimation of perfusion of approximately 17 ± 6% (P < 0.001) occurs in gray matter, when comparing an ROI with a PBP analysis over a group of 12 healthy subjects. Conclusion Analysis of ASL data based on a large ROI may suffer from inaccuracies arising from a distribution of transit times, implying that averaging of ASL kinetic data over such regions should therefore be avoided. When possible, a PBP fit should be performed. J. Magn. Reson. Imaging 2005;21:676–682. © 2005 Wiley-Liss, Inc.

Several strategies have been proposed to model and remove physiological noise from resting-state fMRI (rs-fMRI) data, particularly at ultrahigh fields (7 Tesla), including contributions from respiratory volume (RV) and heart rate (HR) signal fluctuations. Recent studies suggest that these contributions are highly variable across subjects and that physiological noise correction may thus benefit from optimization at the subject or even voxel level. Here, we systematically investigated the impact of the degree of spatial specificity (group, subject, newly proposed cluster, and voxel levels) on the optimization of RV and HR models. For each degree of spatial specificity, we measured the fMRI signal variance explained (VE) by each model, as well as the functional connectivity underlying three well-known resting-state networks (RSNs) obtained from the fMRI data after removal of RV+HR contributions. Whole-brain, high-resolution rs-fMRI data were acquired from twelve healthy volunteers at 7 Tesla, while simultaneously recording their cardiac and respiratory signals. Although VE increased with spatial specificity up to the voxel level, the accuracy of functional connectivity measurements improved only up to the cluster level, and subsequently decreased at the voxel level. This suggests that voxelwise modeling over-fits to local fluctuations with no physiological meaning. In conclusion, our results indicate that 7 Tesla rs-fMRI connectivity measurements improve if a cluster-based physiological noise correction approach is employed in order to take into account the individual spatial variability in the HR and RV contributions.

The study of spontaneous brain activity based on BOLD-fMRI may be seriously compromised by the presence of signal fluctuations of non-neuronal origin, most prominently due to cardiac and respiratory mechanisms. Methods used for modeling and correction of the so-called physiological noise usually rely on the concurrent measurement of cardiac and respiratory signals. In simultaneous EEG-fMRI recordings, which are primarily aimed at the study of spontaneous brain activity, the electrocardiogram (ECG) is typically measured as part of the EEG setup but respiratory data are not generally available. Here, we propose to use the ECG-derived respiratory (EDR) signal estimated by Empirical Mode Decomposition (EMD) as a surrogate of the respiratory signal, for retrospective physiological noise correction of typical simultaneous EEG-fMRI data. A physiological noise model based on these physiological signals (P-PNM) complemented with fMRI-derived noise regressors was generated, and evaluated, for 17 simultaneous EEG-fMRI datasets acquired from a group of seven epilepsy patients imaged at 3T. The respiratory components of P-PNM were found to explain BOLD variance significantly in addition to the cardiac components, suggesting that the EDR signal was successfully extracted from the ECG, and P-PNM outperformed an image-based model (I-PNM) in terms of total BOLD variance explained. Further, the impact of the correction using P-PNM on fMRI mapping of patient-specific epileptic networks and the resting-state default mode network (DMN) was assessed in terms of sensitivity and specificity and, when compared with an ICA-based procedure and a standard pre-processing pipeline, P-PNM achieved the best performance. Overall, our results support the feasibility and utility of extracting physiological noise models of the BOLD signal resorting to ECG data exclusively, with substantial impact on the simultaneous EEG-fMRI mapping of resting-state networks, and, most importantly, epileptic networks where sensitivity and specificity are still limited.

Simultaneous EEG–fMRI offers the possibility of non-invasively studying the spatiotemporal dynamics of epileptic activity propagation from the focus towards an extended brain network, through the identification of the haemodynamic correlates of ictal electrical discharges. In epilepsy associated with hypothalamic hamartomas (HH), seizures are known to originate in the HH but different propagation pathways have been proposed. Here, Dynamic Causal Modelling (DCM) was employed to estimate the seizure propagation pathway from fMRI data recorded in a HH patient, by testing a set of clinically plausible network connectivity models of discharge propagation. The model consistent with early propagation from the HH to the temporal–occipital lobe followed by the frontal lobe was selected as the most likely model to explain the data. Our results demonstrate the applicability of DCM to investigate patient-specific effective connectivity in epileptic networks identified with EEG–fMRI. In this way, it is possible to study the propagation pathway of seizure activity, which has potentially great impact in the decision of the surgical approach for epilepsy treatment., Highlights ► Seizure EEG–fMRI data of a hypothalamic hamartoma epileptic patient was analysed. ► Two competing hypotheses for seizure propagation pathways were tested. ► DCM was used to estimate all plausible connectivity models of seizure propagation. ► Bayesian model selection yielded a model consistent with previous evidence. ► This study provides the first application of DCM to EEG–fMRI data of human seizures.

In this study, we introduce a new approach to process simultaneous Electroencephalography and functional Magnetic Resonance Imaging (EEG‐fMRI) data in epilepsy. The method is based on the decomposition of the EEG signal using independent component analysis (ICA) and the usage of the relevant components' time courses to define the event related model necessary to find the regions exhibiting fMRI signal changes related to interictal activity. This approach achieves a natural data‐driven differentiation of the role of distinct types of interictal activity with different amplitudes and durations in the epileptogenic process. Agreement between the conventional method and this new approach was obtained in 6 out of 9 patients that had interictal activity inside the scanner. In all cases, the maximum Z‐score was greater in the fMRI studies based on ICA component method and the extent of activation was increased in 5 out of the 6 cases in which overlap was found. Furthermore, the three cases where an agreement was not found were those in which no significant activation was found at all using the conventional approach. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.

The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artifact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artifact occurrences using an Optimal Basis Set (OBS) or Average Artifact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artifact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3T and 7T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artifact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3T/7T. Although more significant improvements were achieved at 7T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations.