Broad clinical involvement in a family affected by the fragile X premutation

The mutations in the FMR1 gene have been described as a family of disorders called fragile X-associated disorders including fragile X syndrome, fragile X-associated tremor/ataxia syndrome, primary ovarian insufficiency, and other problems associated with the premutation, such as hypothyroidism, hypertension, neuropathy, anxiety, depression, attention-deficit hyperactivity disorders, and autism spectrum disorders. The premutation is relatively common in the general population affecting 1 of 130 to 250 female individuals and 1 of 250 to 800 male individuals. Therefore, to provide appropriate treatment and genetic counseling for all of the carriers and affected individuals in a family, a detailed family history that reviews many of the disorders that are related to both the premutation and the full mutation should be carried out as exemplified in these cases. To facilitate the integration of this knowledge into clinical practice, this is the first case report that demonstrates only premutation involvement across 3 generations

InfectionCMA: A Cell MicroArray Approach for Efficient Biomarker Screening in In Vitro Infection Assays

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has forced the scientific community to acquire knowledge in real-time, when total lockdowns and the interruption of flights severely limited access to reagents as the global pandemic became established. This unique reality made researchers aware of the importance of designing efficient in vitro set-ups to evaluate infectious kinetics. Here, we propose a histology-based method to evaluate infection kinetics grounded in cell microarray (CMA) construction, immunocytochemistry and in situ hybridization techniques. We demonstrate that the chip-like organization of the InfectionCMA has several advantages, allowing side-by-side comparisons between diverse cell lines, infection time points, and biomarker expression and cytolocalization evaluation in the same slide. In addition, this methodology has the potential to be easily adapted for drug screening. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Funding text 1: Funding: The Portuguese Foundation for Science and Technology (FCT) funded this project through the Research4COVID19 projects 109_596696487 and RESEARCH COVID-19 projects Ref. 510. FCT also financed the Ph.D. grant to R.J.P. (SFRH/BD/145217/2019) and M.N. (2020.04720.BD). i3S is supported by FEDER–Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020–Operational Program for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT/Ministério da Ciência, Tecnologia e Inovação in the framework of the project ‘Institute for Research and Innovation in Health Sciences’ (POCI-01-0145-FEDER-007274).; Funding text 2: The Portuguese Foundation for Science and Technology (FCT) funded this project through the Research4COVID19 projects 109_596696487 and RESEARCH COVID-19 projects Ref. 510. FCT also financed the Ph.D. grant to R.J.P. (SFRH/BD/145217/2019) and M.N. (2020.04720.BD). i3S is supported by FEDER?Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020?Operational Program for Competitiveness and Internationalization (POCI), Portugal 2020, and by Portuguese funds through FCT/Minist?rio da Ci?ncia, Tecnologia e Inova??o in the framework of the project ?Institute for Research and Innovation in Health Sciences? (POCI-01-0145-FEDER-007274)

Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction

Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size. In this study, we evaluate 3D-convolutional neural networks (CNNs) and classical regression methods with hand-crafted features for survival time regression of patients with high grade brain tumors. The tested CNNs for regression showed promising but unstable results. The best performing deep learning approach reached an accuracy of 51.5% on held-out samples of the training set. All tested deep learning experiments were outperformed by a Support Vector Classifier (SVC) using 30 radiomic features. The investigated features included intensity, shape, location and deep features. The submitted method to the BraTS 2018 survival prediction challenge is an ensemble of SVCs, which reached a cross-validated accuracy of 72.2% on the BraTS 2018 training set, 57.1% on the validation set, and 42.9% on the testing set. The results suggest that more training data is necessary for a stable performance of a CNN model for direct regression from magnetic resonance images, and that non-imaging clinical patient information is crucial along with imaging information.Comment: Contribution to The International Multimodal Brain Tumor Segmentation (BraTS) Challenge 2018, survival prediction tas

Serum amyloid A proteins reduce bone mass during mycobacterial infections

IntroductionOsteopenia has been associated to several inflammatory conditions, including mycobacterial infections. How mycobacteria cause bone loss remains elusive, but direct bone infection may not be required. MethodsGenetically engineered mice and morphometric, transcriptomic, and functional analyses were used. Additionally, inflammatory mediators and bone turnover markers were measured in the serum of healthy controls, individuals with latent tuberculosis and patients with active tuberculosis. Results and discussionWe found that infection with Mycobacterium avium impacts bone turnover by decreasing bone formation and increasing bone resorption, in an IFN gamma- and TNF alpha-dependent manner. IFN gamma produced during infection enhanced macrophage TNF alpha secretion, which in turn increased the production of serum amyloid A (SAA) 3. Saa3 expression was upregulated in the bone of both M. avium- and M. tuberculosis-infected mice and SAA1 and 2 proteins (that share a high homology with murine SAA3 protein) were increased in the serum of patients with active tuberculosis. Furthermore, the increased SAA levels seen in active tuberculosis patients correlated with altered serum bone turnover markers. Additionally, human SAA proteins impaired bone matrix deposition and increased osteoclastogenesis in vitro. Overall, we report a novel crosstalk between the cytokine-SAA network operating in macrophages and bone homeostasis. These findings contribute to a better understanding of the mechanisms of bone loss during infection and open the way to pharmacological intervention. Additionally, our data and disclose SAA proteins as potential biomarkers of bone loss during infection by mycobacteria.This article is a result of the project HEALTH-UNORTE: Setting-up biobanks and regenerative medicine strategies to boost research in cardiovascular, musculoskeletal, neurological, oncological, immunological and infectious diseases (NORTE-01-0145-FEDER-000039), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). This work was supported by KOG-202108-00929 from the European Haematology Society, awarded to AG. Work in the MS lab was financed by FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and by Portuguese funds through FCT - Fundacao para a Ciencia e a Tecnologia/Ministerio da Ciencia, Tecnologia e Ensino Superior in the framework of the project POCI-01-0145-FEDER-028955 (PTDC/SAU-INF/28955/2017). AG and MS are supported by an Individual Scientific Employment contract (CEECIND/00048/2017; CEECIND/00241/2017 respectively). DS acknowledges the Portuguese Foundation for Science and Technology (FCT) for the Post-Doc fellowship (SFRH/BPD/115341/2016). RP, DS and AF have PhD grants (SFRH/BD/145217/2019; SFRH/BD/143536/2019; 2020.05949.BD, respectively) financed by FCT

A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative

Computational creativity is a flourishing research area, with a variety of creative systems being produced and developed. Creativity evaluation has not kept pace with system development with an evident lack of systematic evaluation of the creativity of these systems in the literature. This is partially due to difficulties in defining what it means for a computer to be creative; indeed, there is no consensus on this for human creativity, let alone its computational equivalent. This paper proposes a Standardised Procedure for Evaluating Creative Systems (SPECS). SPECS is a three-step process: stating what it means for a particular computational system to be creative, deriving and performing tests based on these statements. To assist this process, the paper offers a collection of key components of creativity, identified empirically from discussions of human and computational creativity. Using this approach, the SPECS methodology is demonstrated through a comparative case study evaluating computational creativity systems that improvise music

Pancreatitis with an unusual fatal complication following endoscopic retrograde cholangiopancreaticography: a case report

<p>Abstract</p> <p>Introduction</p> <p>Endoscopic retrograde cholangiopancreaticography has been the treatment of choice for stones in the common bile duct. Although the procedure is usually safe, procedure-related complications do occur.</p> <p>Case presentation</p> <p>A case of pancreatitis following endoscopic retrograde cholangiopancreaticography is described in a 55-year-old woman. After an uneventful recovery the patient's condition deteriorated rapidly 16 days after the endoscopic retrograde cholangiopancreaticography, and the patient died within 1 hour. Post-mortem examination revealed massive intrapulmonary fat embolism. The complications of endoscopic retrograde cholangiopancreaticography and pancreatitis are described.</p> <p>Conclusion</p> <p>Fat embolism can occur after the remission of pancreatitis and pancreatic necrosis may be overlooked on contrast-enhanced computed tomography scanning.</p

Pyrokinin β-Neuropeptide Affects Necrophoretic Behavior in Fire Ants (S. invicta), and Expression of β-NP in a Mycoinsecticide Increases Its Virulence

Fire ants are one of the world's most damaging invasive pests, with few means for their effective control. Although ecologically friendly alternatives to chemical pesticides such as the insecticidal fungus Beauveria bassiana have been suggested for the control of fire ant populations, their use has been limited due to the low virulence of the fungus and the length of time it takes to kill its target. We present a means of increasing the virulence of the fungal agent by expressing a fire ant neuropeptide. Expression of the fire ant (Solenopsis invicta) pyrokinin β -neuropeptide (β-NP) by B. bassiana increased fungal virulence six-fold towards fire ants, decreased the LT50, but did not affect virulence towards the lepidopteran, Galleria mellonella. Intriguingly, ants killed by the β-NP expressing fungus were disrupted in the removal of dead colony members, i.e. necrophoretic behavior. Furthermore, synthetic C-terminal amidated β-NP but not the non-amidated peptide had a dramatic effect on necrophoretic behavior. These data link chemical sensing of a specific peptide to a complex social behavior. Our results also confirm a new approach to insect control in which expression of host molecules in an insect pathogen can by exploited for target specific augmentation of virulence. The minimization of the development of potential insect resistance by our approach is discussed

Spatial variability of chemical attributes in Latosol and Argisol

The objective of this research was to characterize the spatial variability of chemical attributes of soils cultivated with sugarcane in areas with variations in relief forms. The two soils studied were a Latosol, placed in a convex landform (158ha), and an Argisol, placed in a linear landform (172ha). Soil samples for chemical analysis were collected in a regular grid, at the depth of 0.0-0.5m. The convex landform presented the highest coefficient variation and ranges. Therefore, the Latosol inserted in the landform convex presented greater spatial variability for chemical attributes than the Argisol in the linear landform. A larger number of points must be sampled in order to represent the spatial variability of the Latosol from the convex landform. We recommend the sampling interval to be equal to the range of the spatial dependency in order to associate a less intensive sampling effort with a higher representativity.3851266127