The cortical thickness of tricenarian cocaine users assembles features of an octogenarian brain.

It has been suggested that substance use disorders could lead to accelerated biological aging, but only a few neuroimaging studies have investigated this hypothesis so far. In this cross-sectional study, structural neuroimaging was performed to measure cortical thickness (CT) in tricenarian adults with cocaine use disorder (CUD, n1 = 30) and their age-paired controls (YC, n1 = 30), and compare it with octogenarian elder controls (EC, n1 = 20). We found that CT in the right fusiform gyrus was similar between CUD and EC, thinner than the expected values of YC. We also found that regarding CT of the right inferior temporal gyrus, right inferior parietal cortex, and left superior parietal cortex, the CUD group exhibited parameters that fell in between EC and YC groups. Finally, CT of the right pars triangularis bordering with orbitofrontal gyrus, right superior temporal gyrus, and right precentral gyrus were reduced in CUD when contrasted with YC, but those areas were unrelated to CT of EC. Despite the 50-year age gap between our age groups, CT of tricenarian cocaine users assembles features of an octogenarian brain, reinforcing the accelerated aging hypothesis in CUD.

Interleukin-27 Promotes Divergent Effects on HIV-1 Infection in Peripheral Blood Mononuclear Cells through BST-2/Tetherin.

Interleukin-27 (IL-27) is able to inhibit HIV-1 replication in peripheral blood mononuclear cells (PBMCs), macrophages, and dendritic cells. Here, we identify that IL-27 can produce opposing effects on HIV-1 replication in PBMCs and that the HIV-1 restriction factor BST-2/Tetherin is involved in both inhibitory and enhancing effects on HIV-1 infection induced by IL-27. IL-27 inhibited HIV-1 replication when added to cells 2 h after infection, promoting the prototypical BST-2/Tetherin-induced virion accumulation at the cell membrane of HIV-1-infected PBMCs. BST-2/Tetherin gene expression was significantly upregulated in the IL-27-treated PBMCs, with a simultaneous increase in the number of BST-2/Tetherin+ cells. The silencing of BST-2/Tetherin diminished the anti-HIV-1 effect of IL-27. In contrast, IL-27 increased HIV-1 production when added to infected cells 4 days after infection. This enhancing effect was prevented by BST-2/Tetherin gene knockdown, which also permitted IL-27 to function again as an HIV-1 inhibitory factor. These contrasting roles of IL-27 were associated with the dynamic of viral production, since the IL-27-mediated enhancement of virus replication was prevented by antiretroviral treatment of infected cells, as well as by keeping cells under agitation to avoid cell-to-cell contact. Likewise, inhibition of CD11a, an integrin associated with HIV-1 cell-to-cell transmission, abrogated the IL-27 enhancement of HIV-1 production. Our findings illustrate the complexity of the HIV-1-host interactions and may impact the potential therapeutic use of IL-27 and other soluble mediators that induce BST-2/Tetherin expression for HIV-1 infection. IMPORTANCE Here, we describe new findings related to the ability of the cytokine IL-27 to regulate the growth of HIV-1 in CD4+ T lymphocytes. IL-27 has long been considered a potent inhibitor of HIV-1 replication, a notion based on several reports showing that this cytokine controls HIV-1 infection in peripheral blood mononuclear cells (PBMCs), monocyte-derived macrophages, and dendritic cells. However, our present results are contrary to the current knowledge that IL-27 acts only as a powerful downregulator of HIV-1 replication. We observed that IL-27 can either prevent or enhance viral growth in PBMCs, an outcome dependent on when this cytokine is added to the infected cells. We detected that the increase of HIV-1 dissemination is due to enhanced cell-to-cell transmission with the involvement of the interferon-induced HIV-1 restriction factor BST-2/Tetherin and CD11a (LFA-1), an integrin that participates in formation of virological synapse.

Referenceless Nyquist ghost correction outperforms standard navigator-based method and improves efficiency of in vivo diffusion tensor cardiovascular magnetic resonance.

PURPOSE: The study aims to assess the potential of referenceless methods of EPI ghost correction to accelerate the acquisition of in vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) data using both computational simulations and data from in vivo experiments. METHODS: Three referenceless EPI ghost correction methods were evaluated on mid-ventricular short axis DT-CMR spin echo and STEAM datasets from 20 healthy subjects at 3T. The reduced field of view excitation technique was used to automatically quantify the Nyquist ghosts, and DT-CMR images were fit to a linear ghost model for correction. RESULTS: Numerical simulation showed the singular value decomposition (SVD) method is the least sensitive to noise, followed by Ghost/Object method and entropy-based method. In vivo experiments showed significant ghost reduction for all correction methods, with referenceless methods outperforming navigator methods for both spin echo and STEAM sequences at b = 32, 150, 450, and 600 smm - 2 $$ {\mathrm{smm}}^{-2} $$ . It is worth noting that as the strength of the diffusion encoding increases, the performance gap between the referenceless method and the navigator-based method diminishes. CONCLUSION: Referenceless ghost correction effectively reduces Nyquist ghost in DT-CMR data, showing promise for enhancing the accuracy and efficiency of measurements in clinical practice without the need for any additional reference scans.

Effect of Wave Dark Matter on Equal Mass Black Hole Mergers.

For dark matter to be detectable with gravitational waves from binary black holes, it must reach higher than average densities in their vicinity. In the case of light (wavelike) dark matter, the density of dark matter between the binary can be significantly enhanced by accretion from the surrounding environment. Here we show that the resulting dephasing effect on the last ten orbits of an equal mass binary is maximized when the Compton wavelength of the scalar particle is comparable to the orbital separation, 2π/µâˆ¼d. The phenomenology of the effect is different from the channels that are usually discussed, where dynamical friction (along the orbital path) and radiation of energy and angular momentum drive the dephasing, and is rather dominated by the radial force (the spacetime curvature in the radial direction) towards the overdensity between the black holes. While our numerical studies limit us to scales of the same order, this effect may persist at larger separations and/or particle masses, playing a significant role in the merger history of binaries.

A systematic evaluation of deep learning methods for the prediction of drug synergy in cancer.

One of the main obstacles to the successful treatment of cancer is the phenomenon of drug resistance. A common strategy to overcome resistance is the use of combination therapies. However, the space of possibilities is huge and efficient search strategies are required. Machine Learning (ML) can be a useful tool for the discovery of novel, clinically relevant anti-cancer drug combinations. In particular, deep learning (DL) has become a popular choice for modeling drug combination effects. Here, we set out to examine the impact of different methodological choices on the performance of multimodal DL-based drug synergy prediction methods, including the use of different input data types, preprocessing steps and model architectures. Focusing on the NCI ALMANAC dataset, we found that feature selection based on prior biological knowledge has a positive impact-limiting gene expression data to cancer or drug response-specific genes improved performance. Drug features appeared to be more predictive of drug response, with a 41% increase in coefficient of determination (R2) and 26% increase in Spearman correlation relative to a baseline model that used only cell line and drug identifiers. Molecular fingerprint-based drug representations performed slightly better than learned representations-ECFP4 fingerprints increased R2 by 5.3% and Spearman correlation by 2.8% w.r.t the best learned representations. In general, fully connected feature-encoding subnetworks outperformed other architectures. DL outperformed other ML methods by more than 35% (R2) and 14% (Spearman). Additionally, an ensemble combining the top DL and ML models improved performance by about 6.5% (R2) and 4% (Spearman). Using a state-of-the-art interpretability method, we showed that DL models can learn to associate drug and cell line features with drug response in a biologically meaningful way. The strategies explored in this study will help to improve the development of computational methods for the rational design of effective drug combinations for cancer therapy.

The effects of field strength on stimulated echo and motion-compensated spin-echo diffusion tensor cardiovascular magnetic resonance sequences.

BACKGROUND: In-vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) is an emerging technique for microstructural tissue characterization in the myocardium. Most studies are performed at 3T, where higher signal-to-noise ratio (SNR) should benefit this signal-starved method. However, a few studies have suggested that DT-CMR is possible at 1.5T, where echo planar imaging artifacts may be less severe and 1.5T hardware is more widely available. METHODS: We recruited 20 healthy volunteers and performed mid-ventricular short-axis DT-CMR at 1.5T and 3T. Acquisitions were performed at peak systole and end-diastole using both stimulated echo acquisition mode (STEAM) and motion-compensated spin-echo (MCSE) sequences at matched spatial resolutions. DT-CMR parameters were averaged over the left ventricle and compared between 1.5T and 3T sequences using both datasets with and without the blow reference data included. RESULTS: Eleven (1.5T) and 12 (3T) diastolic MCSE acquisitions were rejected as the helix angle (HA) demonstrated <50% normal appearance circumferentially or the acquisition was abandoned due to poor image quality; a maximum of one acquisition was rejected for other datasets. Subjective HA map quality was significantly better at 3T than 1.5T for STEAM (p < 0.05), but not for MCSE and other DT-CMR quality measures were consistent with improvements in STEAM at 3T over 1.5T. When blow data were excluded, no significant differences in mean diffusivity were observed between field strengths, but fractional anisotropy was significantly higher at 1.5T than 3T for STEAM systole (p < 0.05). Absolute second eigenvector orientation (E2A, sheetlet angle) was significantly higher at 1.5T than 3T for MCSE systole and STEAM diastole, but significantly lower for STEAM systole (all p < 0.05). Transmural HA distribution was less steep at 1.5T than 3T for STEAM diastole data (p < 0.05). SNR was higher at 3T than 1.5T for all acquisitions (p < 0.05). CONCLUSION: While 3T provides benefits in terms of SNR, both STEAM and MCSE can be performed at 1.5T. However, MCSE is unreliable in diastole at both field strengths and STEAM benefits from the improved SNR at 3T over 1.5T. Future clinical research studies may be able to leverage the wider availability of 1.5T CMR hardware where MCSE acquisitions are desirable.

DszA Catalyzes C-S Bond Cleavage through N5-Hydroperoxyl Formation.

Due to its detrimental impact on human health and the environment, regulations demand ultralow sulfur levels on fossil fuels, in particular in diesel. However, current desulfurization techniques are expensive and cannot efficiently remove heteroaromatic sulfur compounds, which are abundant in crude oil and concentrate in the diesel fraction after distillation. Biodesulfurization via the four enzymes of the metabolic 4S pathway of the bacterium Rhodococcus erythropolis (DszA-D) is a possible solution. However, the 4S pathway needs to operate at least 500 times faster for industrial applicability, a goal currently pursued through enzyme engineering. In this work, we unveil the catalytic mechanism of the flavin monooxygenase DszA. Surprisingly, we found that this enzyme follows a recently proposed atypical mechanism that passes through the formation of an N5OOH intermediate at the re side of the cofactor, aided by a well-defined, predominantly hydrophobic O2 pocket. Besides clarifying the unusual chemical mechanism of the complex DszA enzyme, with obvious implications for understanding the puzzling chemistry of flavin-mediated catalysis, the result is crucial for the rational engineering of DszA, contributing to making biodesulfurization attractive for the oil refining industry.

STEAM-SASHA: a novel approach for blood- and fat-suppressed native T1 measurement in the right ventricular myocardium.

OBJECTIVE: The excellent blood and fat suppression of stimulated echo acquisition mode (STEAM) can be combined with saturation recovery single-shot acquisition (SASHA) in a novel STEAM-SASHA sequence for right ventricular (RV) native T1 mapping. MATERIALS AND METHODS: STEAM-SASHA splits magnetization preparation over two cardiac cycles, nulling blood signal and allowing fat signal to decay. Breath-hold T1 mapping was performed in a T1 phantom and twice in 10 volunteers using STEAM-SASHA and a modified Look-Locker sequence at peak systole at 3T. T1 was measured in 3 RV regions, the septum and left ventricle (LV). RESULTS: In phantoms, MOLLI under-estimated while STEAM-SASHA over-estimated T1, on average by 3.0% and 7.0% respectively, although at typical 3T myocardial T1 (T1 > 1200 ms) STEAM-SASHA was more accurate. In volunteers, T1 was higher using STEAM-SASHA than MOLLI in the LV and septum (p = 0.03, p = 0.006, respectively), but lower in RV regions (p > 0.05). Inter-study, inter-observer and intra-observer coefficients of variation in all regions were < 15%. Blood suppression was excellent with STEAM-SASHA and noise floor effects were minimal. DISCUSSION: STEAM-SASHA provides accurate and reproducible T1 in the RV with excellent blood and fat suppression. STEAM-SASHA has potential to provide new insights into pathological changes in the RV in future studies.

Impact of dydrogesterone use in cycles with low progesterone levels on the day of frozen embryo transfer.

PURPOSE: This study aims to evaluate whether the clinical outcomes of cycles with frozen embryo transfer (FET) in hormonal replacement treatment supplemented with dydrogesterone (DYD) following detection of low circulating levels of progesterone (P4) were comparable to the results of cycles with otherwise normal serum P4 values. METHODS: Extended analyses of a retrospective cohort that included FET cycles performed between July 2019 and March 2022 after a cycle of artificial endometrial preparation using valerate-estradiol and micronized vaginal P4 (400 mg twice daily). Whenever the serum P4 value was considered low on the morning of the planned transfer, 10 mg of DYD three times a day was added as a supplement. Only single-embryo transfers of a blastocyst were considered. The primary endpoint was live birth rate. RESULTS: Five-hundred thirty-five FET cycles were analyzed, of which 136 (25.4%) underwent treatment with DYD. There were 337 pregnancies (63%), 207 live births (38.6%), and 130 miscarriages (38.5%). The P4 values could be modeled by a gamma distribution, with a mean of 14.5 ng/ml and a standard deviation of 1.95 ng/ml. The variables female age on the day of FET, ethnicity, and weight were associated with a variation in the serum P4 values. There were no differences in the results between cycles with or without the indication for DYD supplementation. CONCLUSIONS: Live birth rate did not vary significantly in females with low and normal serum P4 levels on the day of FET when DYD was used as rescue therapy.

Digital flashcards and medical physiology performance: a dose-dependent effect.

Use of digital flashcards promotes active recall, spaced repetition, and self-assessment academic principles. This work explores the association and dose-dependent effect of this study method and locomotor (LP) and cardiovascular physiology (CP) grades. A single-faculty cohort study of medical LP and CP students was conducted, and 155 and 676 flashcards, respectively, were created through Moodle. An exploratory analysis examined three exam results (2019), and a confirmatory study used a fourth exam (2021) in another CP cohort. Of 685 students enrolled, 558 participated in the exploratory analysis: 319 (69%) for LP and 311 (84%) for CP, of which 203 LP and 267 CP students were flashcard users. Median grades were higher among flashcard users, and the number of cards reviewed was positively correlated with grades (r = 0.275 to 0.388 for LP and r = 0.239 to 0.432 for CP, P < 0.001). Multiple linear regression models confirmed a positive dose-dependent association between results and the number of flashcards studied: for every 100 LP cards reviewed, exam grades increased 0.44-0.75 on a 0-20 scale range (P < 0.001), and for every 1,000 CP flashcards, results raised 0.81-1.08 values (P < 0.05). These findings were confirmed in the 2021 CP cohort of 269 participants, of whom 67% were flashcard users. Digital flashcard revision has a consistent positive dose-dependent association on LP and CP grades.NEW & NOTEWORTHY Implementing flashcard-based strategies is a feasible way to promote active recall, spaced repetition, and self-assessment, and students are highly adherent to these initiatives. There is a positive dose-dependent association between the number of flashcards reviewed and physiology grades. These results are consistent across different physiology subjects, under different cohorts, over short and medium terms.

Multiple Lines of Evidence Support 199 SARS-CoV-2 Positively Selected Amino Acid Sites.

SARS-CoV-2 amino acid variants that contribute to an increased transmissibility or to host immune system escape are likely to increase in frequency due to positive selection and may be identified using different methods, such as codeML, FEL, FUBAR, and MEME. Nevertheless, when using different methods, the results do not always agree. The sampling scheme used in different studies may partially explain the differences that are found, but there is also the possibility that some of the identified positively selected amino acid sites are false positives. This is especially important in the context of very large-scale projects where hundreds of analyses have been performed for the same protein-coding gene. To account for these issues, in this work, we have identified positively selected amino acid sites in SARS-CoV-2 and 15 other coronavirus species, using both codeML and FUBAR, and compared the location of such sites in the different species. Moreover, we also compared our results to those that are available in the COV2Var database and the frequency of the 10 most frequent variants and predicted protein location to identify those sites that are supported by multiple lines of evidence. Amino acid changes observed at these sites should always be of concern. The information reported for SARS-CoV-2 can also be used to identify variants of concern in other coronaviruses.

The longitudinal effect of the quality of participation experiences in a voluntary organization on youth psychological empowerment.

Research shows its limitations by not capturing the specificities of individual experiences, which result either from the participation of or interaction among different people in a given context across time. This study explores the effect that the quality of youth participation experiences in a Portuguese voluntary organization can have on the development of their psychological empowerment (PE). This study adopted a longitudinal, quantitative design where the same cohort of 481 participants (62.4% female; Mage = 17.26 years) was followed across three time points. Latent growth curve modeling was performed to examine the effect of the quality of participation experiences (QPE) on the developmental trajectories of PE components. Findings show that the QPE had the most powerful effect on developmental trajectories in PE. The study shows how youth perceptions of opportunities for reflection and action in interaction in a climate of openness to dialogue and the emergence of different ways of thinking and doing affect their PE.

Deep learning for drug response prediction in cancer.

Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of paramount importance for precision medicine. Machine learning(ML) algorithms can be trained on high-throughput screening data to develop models that are able to predict the response of cancer cell lines and patients to novel drugs or drug combinations. Deep learning (DL) refers to a distinct class of ML algorithms that have achieved top-level performance in a variety of fields, including drug discovery. These types of models have unique characteristics that may make them more suitable for the complex task of modeling drug response based on both biological and chemical data, but the application of DL to drug response prediction has been unexplored until very recently. The few studies that have been published have shown promising results, and the use of DL for drug response prediction is beginning to attract greater interest from researchers in the field. In this article, we critically review recently published studies that have employed DL methods to predict drug response in cancer cell lines. We also provide a brief description of DL and the main types of architectures that have been used in these studies. Additionally, we present a selection of publicly available drug screening data resources that can be used to develop drug response prediction models. Finally, we also address the limitations of these approaches and provide a discussion on possible paths for further improvement. Contact:  mrocha@di.uminho.pt.

Realistic numerical simulations of diffusion tensor cardiovascular magnetic resonance: The effects of perfusion and membrane permeability.

PURPOSE: To study the sensitivity of diffusion tensor cardiovascular magnetic resonance (DT-CMR) to microvascular perfusion and changes in cell permeability. METHODS: Monte Carlo (MC) random walk simulations in the myocardium have been performed to simulate self-diffusion of water molecules in histology-based media with varying extracellular volume fraction (ECV) and permeable membranes. The effect of microvascular perfusion on simulations of the DT-CMR signal has been incorporated by adding the contribution of particles traveling through an anisotropic capillary network to the diffusion signal. The simulations have been performed considering three pulse sequences with clinical gradient strengths: monopolar stimulated echo acquisition mode (STEAM), monopolar pulsed-gradient spin echo (PGSE), and second-order motion-compensated spin echo (MCSE). RESULTS: Reducing ECV intensifies the diffusion restriction and incorporating membrane permeability reduces the anisotropy of the diffusion tensor. Widening the intercapillary velocity distribution results in increased measured diffusion along the cardiomyocytes long axis when the capillary networks are anisotropic. Perfusion amplifies the mean diffusivity for STEAM while the opposite is observed for short diffusion encoding time sequences (PGSE and MCSE). CONCLUSION: The effect of perfusion on the measured diffusion tensor is reduced using an increased reference b-value. Our results pave the way for characterization of the response of DT-CMR to microstructural changes underlying cardiac pathology and highlight the higher sensitivity of STEAM to permeability and microvascular circulation due to its longer diffusion encoding time.

Animal Fatty Acid Synthase: A Chemical Nanofactory.

Fatty acids are crucial molecules for most living beings, very well spread and conserved across species. These molecules play a role in energy storage, cell membrane architecture, and cell signaling, the latter through their derivative metabolites. De novo synthesis of fatty acids is a complex chemical process that can be achieved either by a metabolic pathway built by a sequence of individual enzymes, such as in most bacteria, or by a single, large multi-enzyme, which incorporates all the chemical capabilities of the metabolic pathway, such as in animals and fungi, and in some bacteria. Here we focus on the multi-enzymes, specifically in the animal fatty acid synthase (FAS). We start by providing a historical overview of this vast field of research. We follow by describing the extraordinary architecture of animal FAS, a homodimeric multi-enzyme with seven different active sites per dimer, including a carrier protein that carries the intermediates from one active site to the next. We then delve into this multi-enzyme's detailed chemistry and critically discuss the current knowledge on the chemical mechanism of each of the steps necessary to synthesize a single fatty acid molecule with atomic detail. In line with this, we discuss the potential and achieved FAS applications in biotechnology, as biosynthetic machines, and compare them with their homologous polyketide synthases, which are also finding wide applications in the same field. Finally, we discuss some open questions on the architecture of FAS, such as their peculiar substrate-shuttling arm, and describe possible reasons for the emergence of large megasynthases during evolution, questions that have fascinated biochemists from long ago but are still far from answered and understood.

Judicialization and cancer: quality of life of patients and caregivers in the COVID-19 pandemic.

BACKGROUND: In Brazil, cancer patients and caregivers of cancer patients seek judicial intervention for free access to medications from the public health system. Indeed, the COVID-19 pandemic potentially affected the health-related quality of life of cancer patients and caregivers of cancer patients. This study aimed to describe the sociodemographic profile and assess the health-related quality of life of patients and caregivers in the state of Goias, Brazil, in 2020. METHODS: A cross-sectional study was conducted using the Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) and a sociodemographic questionnaire. RESULTS: A total of 88 (67,7%) patients and 42 (32,3%) caregivers participated in the study, mostly women (55,5%); aged from 18 to 60 (66%) years old; with up to nine years of education (73,1%) and monthly family income lower than the minimum wage (69,2%); married or in a stable union (92,3%); living with multiple people in the same household (73,8%). The quality of life domains with the best scores were mental health for patients and pain for caregivers. The most affected quality of life domain was physical limitation for patients and caregivers. Factors associated with better quality of life were female gender and age between 18 and 60 years in patients, more than 9 years of education, living with multiple people in the same house, and having a monthly family income higher than US$200 for caregivers. CONCLUSION: The study found evidence of physical and emotional vulnerability during the pandemic, highlighting the need to strengthen public policies of assistance support to this population.

Impact of a wearable-based physical activity and sleep intervention in multimorbidity patients: protocol for a randomized controlled trial.

BACKGROUND: The benefits of physical activity (PA) and adequate sleep are well documented, and their importance strengthens with the increasing prevalence of chronic diseases and multimorbidity (MM). Interventions to promote physical activity and sleep that use commercial activity trackers may be useful non-pharmacological approaches to managing individual health; however, limited evidence exists on their use to improve physical activity in older adult patients with MM. METHODS: This study aims to measure the effects of behavioral change techniques (BCTs) delivered by a wearable device on physical activity and quality of sleep (QS) in older adult patients with MM. We designed an open-label randomized controlled trial with participants recruited through primary care and a specialist outpatient clinic. Participants must be more than 65 years old, have MM, and have access to smartphones. All eligible participants will receive PA promotion content and will be randomly assigned to wear a smartwatch. The primary outcome will be the participants' PA measurement at baseline and at six months using the International Physical Activity Questionnaire - Short Form (IPAQ-SF). Secondary outcomes will include changes in the participants' frailty status, biometric measurements, quality of life, and biopsychosocial assessments. A sample size of 40 participants per arm was calculated to detect group differences, with 50 participants planned to recruit and randomize into each arm. DISCUSSION: This study aims to contribute to a better understanding of PA patterns and the impact of wearable-based PA interventions in patients with MM. In addition, we aim to contribute to more knowledge about the relationship between PA patterns, Patient Reported Outcomes Measures (PROMs), and healthcare resource utilization in patients with MM. To achieve this, the study will leverage a locally developed PROMs registry and assess data from participants' medical records, in order to understand the added impact of wearable data and medical information data on predicting PROMs and unplanned hospital admissions. TRIAL REGISTRATION: NCT05777291.

Effect of Dietary Incorporation of Yellow Mealworm as a Partial Fishmeal Replacer on Growth, Metabolism, and Intestinal Histomorphology in Juvenile Meagre (Argyrosomus regius).

Efforts have been made to find alternatives to fish meal (FM), as the sustainability of aquaculture depends on it. Insect meal (IM) is a potential candidate to partially replace FM, being more sustainable and economically viable. In this experimental trial, three diets were tested with different yellow mealworm incorporation: a control diet with no IM, a diet with an inclusion of 10% IM (Ins10), and a diet with an incorporation of 20% IM (Ins20). The diets were tested on 10.5 g meagre for 47 days. The results showed that an IM inclusion higher than 10% affected both growth (2.6 vs. 2.2) and FCR (1.5 vs. 1.9) of meagre juveniles. However, this reduction in growth did not result from lower protein retention or changes in muscle fibre area or density. Little differences were observed in the activity of pancreatic and intestinal enzymes except for aminopeptidase total activity which was higher in the control and Ins10 compared to Ins20 (3847 vs. 3540 mU/mg protein), suggesting no limitations in protein synthesis. Also, the alkaline phosphatase intestinal maturation index was higher in the control group compared to the IM groups (437 vs. 296). On the contrary, several differences were also found in the proteolytic activity in the hepatic and muscle tissues of meagre juveniles fed the Ins10 diet. The inclusion of IM had no impact on intestine histomorphology but changes were detected in the enterocytes of fish from control and Ins10 which showed hypervacuolization and nucleus misplacement compared to the Ins20 treatment. Nevertheless, a higher percentage of Vibrionaceae was recorded for meagre fed on the Ins20 diet. Since no signs of inflammation were observed in the distal intestine, this suggests IM incorporation could have had an important impact on intestinal health due to its antimicrobial properties. This is supported by an increase in the haematocrit in the treatments where IM was added (20 to 25%). In conclusion, incorporations of IM at percentages up to 10% do not seem to have a negative impact on meagre performance at this age but can enhance the fish immune system and protection against intestinal inflammation.

Appetitive traits and food groups consumption in school-aged children: prospective associations from the Generation XXI birth cohort.

PURPOSE: Appetite can influence children's dietary choices; however, this relationship in school-aged children is still unclear. We aimed to explore the prospective associations between child appetitive traits at age 7 and food consumption at 10 years of age. METHODS: The study included 3860 children from the Generation XXI birth cohort, recruited in 2005/2006 in Porto, Portugal. The Children's Eating Behaviour Questionnaire was used to evaluate children's appetitive traits at 7 years. Food consumption was measured at 10 years through a validated Food Frequency Questionnaire. Logistic regression models were performed and adjusted for possible confounders. RESULTS: Children with greater Enjoyment of Food at 7 years were 36% more likely to eat fruits ≥ 2 times/day and 54% more likely to eat vegetables > 2.5 times/day at 10 years compared to those with less frequent consumption. Children who ate more in response to negative emotions had higher odds of consuming energy-dense foods (OR = 1.33; 99% CI 1.13-1.58) and salty snacks (OR = 1.28; 99% CI 1.08-1.51) 3 years later. Those with less ability to adjust intake (higher Satiety Responsiveness) and more selective about foods (higher Food Fussiness) at 7 years were less likely to consume vegetables frequently, and were more likely to consume energy-dense foods and sugar-sweetened beverages. CONCLUSIONS: Children's appetitive traits at 7 years were associated with the consumption of several food groups at 10 years of age. Eating more in response to negative emotions (Emotional Eating), with less ability to adjust intake (Satiety Responsiveness) and more food selectivity (Food Fussiness) were associated with worse dietary choices (in general, lower fruit and vegetables, and higher energy-dense foods and sugar-sweetened beverages consumption). LEVEL OF EVIDENCE: Level III: Evidence obtained from well-designed cohort or case-control analytic studies.

Scalable transcriptomics analysis with Dask: applications in data science and machine learning.

BACKGROUND: Gene expression studies are an important tool in biological and biomedical research. The signal carried in expression profiles helps derive signatures for the prediction, diagnosis and prognosis of different diseases. Data science and specifically machine learning have many applications in gene expression analysis. However, as the dimensionality of genomics datasets grows, scalable solutions become necessary. METHODS: In this paper we review the main steps and bottlenecks in machine learning pipelines, as well as the main concepts behind scalable data science including those of concurrent and parallel programming. We discuss the benefits of the Dask framework and how it can be integrated with the Python scientific environment to perform data analysis in computational biology and bioinformatics. RESULTS: This review illustrates the role of Dask for boosting data science applications in different case studies. Detailed documentation and code on these procedures is made available at https://github.com/martaccmoreno/gexp-ml-dask . CONCLUSION: By showing when and how Dask can be used in transcriptomics analysis, this review will serve as an entry point to help genomic data scientists develop more scalable data analysis procedures.