Generating multi-pathological and multi-modal images and labels for brain MRI.

The last few years have seen a boom in using generative models to augment real datasets, as synthetic data can effectively model real data distributions and provide privacy-preserving, shareable datasets that can be used to train deep learning models. However, most of these methods are 2D and provide synthetic datasets that come, at most, with categorical annotations. The generation of paired images and segmentation samples that can be used in downstream, supervised segmentation tasks remains fairly uncharted territory. This work proposes a two-stage generative model capable of producing 2D and 3D semantic label maps and corresponding multi-modal images. We use a latent diffusion model for label synthesis and a VAE-GAN for semantic image synthesis. Synthetic datasets provided by this model are shown to work in a wide variety of segmentation tasks, supporting small, real datasets or fully replacing them while maintaining good performance. We also demonstrate its ability to improve downstream performance on out-of-distribution data.

Sleep-Energy: An Energy Optimization Method to Sleep Stage Scoring.

Sleep is essential for physical and mental health. Polysomnography (PSG) procedures are labour-intensive and time-consuming, making diagnosing sleep disorders difficult. Automatic sleep staging using Machine Learning (ML) - based methods has been studied extensively, but frequently provides noisier predictions incompatible with typical manually annotated hypnograms. We propose an energy optimization method to improve the quality of hypnograms generated by automatic sleep staging procedures. The method evaluates the system's total energy based on conditional probabilities for each epoch's stage and employs an energy minimisation procedure. It can be used as a meta-optimisation layer over the sleep stage sequences generated by any classifier that generates prediction probabilities. The method improved the accuracy of state-of-the-art Deep Learning models in the Sleep EDFx dataset by 4.0% and in the DRM-SUB dataset by 2.8%.

Generalizability of 3D CNN models for age estimation in diverse youth populations using structural MRI.

Recently, several studies have investigated the neurodevelopment of psychiatric disorders using brain data acquired via structural magnetic resonance imaging (sMRI). These analyses have shown the potential of sMRI data to provide a relatively precise characterization of brain structural biomarkers. Despite these advances, a relatively unexplored question is how reliable and consistent a model is when assessing subjects from other independent datasets. In this study, we investigate the performance and generalizability of the same model architecture trained from distinct datasets comprising youths in diverse stages of neurodevelopment and with different mental health conditions. We employed models with the same 3D convolutional neural network (CNN) architecture to assess autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), brain age, and a measure of dimensional psychopathology, the Child Behavior Checklist (CBCL) total score. The investigated datasets include the Autism Brain Imaging Data Exchange II (ABIDE-II, N = 580), Attention Deficit Hyperactivity Disorder (ADHD-200, N = 922), Brazilian High-Risk Cohort Study (BHRCS, N = 737), and Adolescent Brain Cognitive Development (ABCD, N = 11,031). Models' performance and interpretability were assessed within each dataset (for diagnosis tasks) and inter-datasets (for age estimation). Despite the demographic and phenotypic differences of the subjects, all models presented significant estimations for age (p value < 0.001) within and between datasets. In addition, most models showed a moderate to high correlation in age estimation. The results, including the models' brain regions of interest (ROI), were analyzed and discussed in light of the youth neurodevelopmental structural changes. Among other interesting discoveries, we found that less confounded training datasets produce models with higher generalization capacity.

Geometry-invariant abnormality detection.

Cancer is a highly heterogeneous condition best visualised in positron emission tomography. Due to this heterogeneity, a general-purpose cancer detection model can be built using unsupervised learning anomaly detection models. While prior work in this field has showcased the efficacy of abnormality detection methods (e.g. Transformer-based), these have shown significant vulnerabilities to differences in data geometry. Changes in image resolution or observed field of view can result in inaccurate predictions, even with significant data pre-processing and augmentation. We propose a new spatial conditioning mechanism that enables models to adapt and learn from varying data geometries, and apply it to a state-of-the-art Vector-Quantized Variational Autoencoder + Transformer abnormality detection model. We showcase that this spatial conditioning mechanism statistically-significantly improves model performance on whole-body data compared to the same model without conditioning, while allowing the model to perform inference at varying data geometries.

Latent Transformer Models for out-of-distribution detection.

Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One popular approach to this challenge is to develop predictive models that can provide a measure of their uncertainty. Another approach is to use generative modelling to quantify the likelihood of inputs. Inputs with a low enough likelihood are deemed to be out-of-distribution and are not presented to the downstream predictive model. In this work, we evaluate several approaches to segmentation with uncertainty for the task of segmenting bleeds in 3D CT of the head. We show that these models can fail catastrophically when operating in the far out-of-distribution domain, often providing predictions that are both highly confident and wrong. We propose to instead perform out-of-distribution detection using the Latent Transformer Model: a VQ-GAN is used to provide a highly compressed latent representation of the input volume, and a transformer is then used to estimate the likelihood of this compressed representation of the input. We demonstrate this approach can identify images that are both far- and near- out-of-distribution, as well as provide spatial maps that highlight the regions considered to be out-of-distribution. Furthermore, we find a strong relationship between an image's likelihood and the quality of a model's segmentation on it, demonstrating that this approach is viable for filtering out unsuitable images.

Estimating Gender and Age from Brain Structural MRI of Children and Adolescents: A 3D Convolutional Neural Network Multitask Learning Model.

Despite recent advances, assessing biological measurements for neuropsychiatric disorders is still a challenge, where confounding variables such as gender and age (as a proxy for neurodevelopment) play an important role. This study explores brain structural magnetic resonance imaging (sMRI) from two public data sets (ABIDE-II and ADHD-200) with healthy control (HC, N = 894), autism spectrum disorder (ASD, N = 251), and attention deficit hyperactivity disorder (ADHD, N = 357) individuals. We used gray and white matter preprocessed via voxel-based morphometry (VBM) to train a 3D convolutional neural network with a multitask learning strategy to estimate gender, age, and mental health status from structural brain differences. Gradient-based methods were employed to generate attention maps, providing clinically relevant identification of most representative brain regions for models' decision-making. This approach resulted in satisfactory predictions for gender and age. ADHD-200-trained models, evaluated in 10-fold cross-validation procedures on test set, obtained a mean absolute error (MAE) of 1.43 years (±0.22 SD) for age prediction and an area under the curve (AUC) of 0.85 (±0.04 SD) for gender classification. In out-of-sample validation, the best-performing ADHD-200 models satisfactorily predicted age (MAE = 1.57 years) and gender (AUC = 0.89) in the ABIDE-II data set. The models' accuracy was in line with the current state-of-the-art machine learning applications in neuroimaging. Key regions for models' accuracy were presented as a meaningful graphical output. New implementations, such as the use of VBM along with a 3D convolutional neural network multitask learning model and a brain imaging graphical output, reinforce the relevance of the proposed workflow.

Papez Circuit Gray Matter and Episodic Memory in Amyotrophic Lateral Sclerosis and Behavioural Variant Frontotemporal Dementia.

Amyotrophic lateral sclerosis and behavioural variant frontotemporal dementia are two different diseases recognized to overlap at clinical, pathological and genetic characteristics. Both conditions are traditionally known for relative sparing of episodic memory. However, recent studies have disputed that with the report of patients presenting with marked episodic memory impairment. Besides that, structural and functional changes in temporal lobe regions responsible for episodic memory processing are often detected in neuroimaging studies of both conditions. In this study, we investigated the gray matter features associated with the Papez circuit in amyotrophic lateral sclerosis, behavioural variant frontotemporal dementia and healthy controls to further explore similarities and differences between the two conditions. Our non-demented amyotrophic lateral sclerosis patients showed no episodic memory deficits measured by a short-term delayed recall test while no changes in gray matter of the Papez circuit were found. Compared with the amyotrophic lateral sclerosis group, the behavioural variant frontotemporal dementia group had lower performance on the short-term delayed recall test and marked atrophy in gray matter of the Papez circuit. Bilateral atrophy of entorhinal cortex and mammillary bodies distinguished behavioural variant frontotemporal dementia from amyotrophic lateral sclerosis patients as well as atrophy in left cingulate, left hippocampus and right parahippocampal gyrus. Taken together, our results suggest that sub-regions of the Papez circuit could be differently affected in amyotrophic lateral sclerosis and behavioural variant frontotemporal dementia.

Isolation and characterization of broadly neutralizing human monoclonal antibodies to the e1 glycoprotein of hepatitis C virus.

The relative importance of humoral and cellular immunity in the prevention or clearance of hepatitis C virus (HCV) infection is poorly understood. However, there is considerable evidence that neutralizing antibodies are involved in disease control. Here we describe the detailed analysis of human monoclonal antibodies (MAbs) directed against HCV glycoprotein E1, which may have the potential to control HCV infection. We have identified two MAbs that can strongly neutralize HCV-pseudotyped particles (HCVpp) bearing the envelope glycoproteins of genotypes 1a, 1b, 4a, 5a, and 6a and less strongly neutralize HCVpp bearing the envelope glycoproteins of genotype 2a. Genotype 3a was not neutralized. The epitopes for both MAbs were mapped to the region encompassing amino acids 313 to 327. In addition, robust neutralization was also observed against cell culture-adapted viruses of genotypes 1a and 2a. Results from this study suggest that these MAbs may have the potential to prevent HCV infection.

Regional Dynamics of the Resting Brain in Amyotrophic Lateral Sclerosis Using Fractional Amplitude of Low-Frequency Fluctuations and Regional Homogeneity Analyses.

Resting-state functional magnetic resonance imaging has been playing an important role in the study of amyotrophic lateral sclerosis (ALS). Although functional connectivity is widely studied, the patterns of spontaneous neural activity of the resting brain are important mechanisms that have been used recently to study a variety of conditions but remain less explored in ALS. Here we have used fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) to study the regional dynamics of the resting brain of nondemented ALS patients compared with healthy controls. As expected, we found the sensorimotor network with changes in fALFF and ReHo, and also found the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) altered and the cerebellum, although no structural changes between ALS patients and controls were reported in the regions with fALFF and ReHo changes. We show an altered pattern in the spontaneous low-frequency oscillations that is not confined to the motor areas and reveal a more widespread involvement of nonmotor regions, including those responsible for cognition.

The extent of vacuolation in non-heart-beating porcine donor liver grafts prior to transplantation predicts their viability.

Livers exposed to prolonged warm ischemia (WI), such as those from non-heart-beating donors (NHBDs), are at higher risk of primary graft nonfunction (PNF). In a pig model of liver transplantation (LTx) from NHBDs, hepatocellular vacuolation, focal hepatocyte dropout, congestion, and sinusoidal dilatation appeared on biopsies taken after exposure to WI. In functioning grafts, vacuolation and sinusoidal dilatation were reversible after LTx, in contrast to PNF grafts. We studied whether the extent of these morphological signs and particularly vacuolation, present on pre-LTx biopsies, was associated with WI length and able to predict PNF, hepatocellular damage, and survival. Pre-LTx biopsies from pig livers exposed to incremental periods of WI were reviewed retrospectively. The extent of vacuolation was quantified blindly by a pathologist's semiquantitative score, validated by stereological point counting and digital image analysis, and then used to predict PNF and hepatocellular damage. On biopsies taken after WI, stereological point counting and digital analysis scoring contributed significantly in predicting PNF (P = 0.027 and P = 0.043, respectively) versus the pathologist's semiquantitative score (P = 0.058). Stereological point counting and digital image analysis predicted the extent of hepatocellular damage (P < 0.0001 and P = 0.001) versus the pathologist's semiquantitative score (P = 0.085). In conclusion, the extent of parenchymal vacuolation present on WI liver grafts reflects the severity of hepatocellular damage and predicts pig liver graft viability before LTx. Further studies are now warranted to evaluate whether these anoxic changes that are associated with liver graft viability in pigs also apply to human NHBD liver biopsies.

Structural and functional papez circuit integrity in amyotrophic lateral sclerosis.

Cognitive impairment in amyotrophic lateral sclerosis (ALS) is heterogeneous but now recognized as a feature in non-demented patients and no longer exclusively attributed to executive dysfunction. However, despite common reports of temporal lobe changes and memory deficits in ALS, episodic memory has been less explored. In the current study, we examined how the Papez circuit-a circuit known to participate in memory processes-is structurally and functionally affected in ALS patients (n = 20) compared with healthy controls (n = 15), and whether these changes correlated with a commonly used clinical measure of episodic memory. Our multimodal MRI approach (cortical volume, voxel-based morphometry, diffusion tensor imaging and resting state functional magnetic resonance) showed reduced gray matter in left hippocampus, left entorhinal cortex and right posterior cingulate as well as increased white matter fractional anisotropy and decreased mean diffusivity in the left cingulum bundle (hippocampal part) of ALS patients compared with controls. Interestingly, thalamus, mammillary bodies and fornix were preserved. Finally, we report a decreased functional connectivity in ALS patients in bilateral hippocampus, bilateral anterior and posterior parahippocampal gyrus and posterior cingulate. The results revealed that ALS patients showed statistically significant structural changes, but more important, widespread prominent functional connectivity abnormalities across the regions comprising the Papez circuit. The decreased functional connectivity found in the Papez network may suggest these changes could be used to assess risk or assist early detection or development of memory symptoms in ALS patients even before structural changes are established.

Investigating brain structural patterns in first episode psychosis and schizophrenia using MRI and a machine learning approach.

In this study, we employed the Maximum Uncertainty Linear Discriminant Analysis (MLDA) to investigate whether the structural brain patterns in first episode psychosis (FEP) patients would be more similar to patients with chronic schizophrenia (SCZ) or healthy controls (HC), from a schizophrenia model perspective. Brain regions volumetric data were estimated by using MRI images of SCZ and FEP patients and HC. First, we evaluated the MLDA performance in discriminating SCZ from controls, which provided a score based on a model for changes in brain structure in SCZ. In the following, we compared the volumetric patterns of FEP patients with patterns of SCZ and healthy controls using these scores. The FEP group had a score distribution more similar to patients with schizophrenia (p-value = .461; Cohen's d=-.15) in comparison with healthy subjects (p-value=.003; Cohen's d = .62). Structures related to the limbic system and the circuitry involved in goal-directed behaviours were the most discriminant regions. There is a distinct pattern of volumetric changes in patients with schizophrenia in contrast to healthy controls, and this pattern seem to be detectable already in FEP.

Multispecies Fisheries in the Lower Amazon River and Its Relationship with the Regional and Global Climate Variability.

This paper aims to describe the spatial-temporal variability in catch of the main fishery resources of the Amazon River and floodplain lakes of the Lower Amazon, as well as relating the Catch per Unit of Effort with anomalies of some of the Amazon River, atmosphere and Atlantic Ocean system variables, determining the influence of the environment on the Amazonian fishery resources. Finfish landings data from the towns and villages of the Lower Amazon for the fisheries of three sites (Óbidos, Santarém and Monte Alegre), were obtained for the period between January 1993 and December 2004. Analysis of variance, detrended correspondence analysis, redundancy analysis and multiple regression techniques were used for the statistical analysis of the distinct time series. Fisheries production in the Lower Amazon presents differences between the Amazon River and the floodplain lakes. Production in the Amazon River is approximately half of the one of the floodplain lakes. This variability occurs both along the Lower Amazon River region (longitudinal gradient) and laterally (latitudinal gradient) for every fishing ground studied here. The distinct environmental variables alone or in association act differently on the fishery stocks and the success of catches in each fishery group studied here. Important variables are the flooding events; the soil the sea surface temperatures; the humidity; the wind and the occurence of El Niño-Southern Oscillation events. Fishery productivity presents a large difference in quantity and distribution patterns between the river and floodplain lakes. This variability occurs in the region of the Lower Amazon as well as laterally for each fishery group studied, being dependent on the ecological characteristics and life strategies of each fish group considered here.

Carbon dioxide fixation in 'Archaeoglobus lithotrophicus': are there multiple autotrophic pathways?

Several representatives of the euryarchaeal class Archaeoglobi are able to grow facultative autotrophically using the reductive acetyl-CoA pathway, with 'Archaeoglobus lithotrophicus' being an obligate autotroph. However, genome sequencing revealed that some species harbor genes for key enzymes of other autotrophic pathways, i.e. 4-hydroxybutyryl-CoA dehydratase of the dicarboxylate/hydroxybutyrate cycle and the hydroxypropionate/hydroxybutyrate cycle and ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) of the Calvin-Benson cycle. This raised the question of whether only one or multiple autotrophic pathways are operating in these species. We searched for the presence of enzyme activities specific for the dicarboxylate/hydroxybutyrate or the hydroxypropionate/hydroxybutyrate cycles in 'A. lithotrophicus', but such enzymes could not be detected. Low Rubisco activity was detected that could not account for the carbon dioxide (CO(2)) fixation rate; in addition, phosphoribulokinase activity was not found. The generation of ribulose 1,5-bisphosphate from 5-phospho-D-ribose 1-pyrophosphate was observed, but not from AMP; these sources for ribulose 1,5-bisphosphate have been proposed before. Our data indicate that the reductive acetyl-CoA pathway is the only functioning CO(2) fixation pathway in 'A. lithotrophicus'.

On the panic reactions of ants to a crushed conspecific: a contribution to a psychoethology of fear

Esmagando-se uma ou mais formigas sobre a trilha da formiga Paratrechina (Nylanderia) fulva Mayr, provocam-se mudanças marcadas no comportamento das outras quando chegam perto da coespecífica morta. Estas "reações de pânico" (desvio, retorno, marcha ondulante, sacolejo e desorientação) representam uma perturbação ou uma desorganização do comportamento que prevalecia na trilha antes da mudança (Cunha, 1967). Na primeira parte do presente trabalho, tentou-se mostrar como a forma e as circunstâncias específicas de cada uma dessas reações são um reflexo da experiência prévia das formigas individuais com a situação posteriormente alterada. Na segunda parte, utilizando-se dados de algumas espécies de formigas de quatro sub-famílias (Myrmicinae, Formicinae, Ponerinae e Dorylinae) sobre a intensidade da reação a coespecíficas esmagadas na trilha, mostrou-se como esta intensidade parece correlacionada, não com a posição taxonômica das espécies consideradas, mas com o grau em que os indivíduos dessas espécies são capazes de atração mútua e de interação num nível propriamente individual. O medo é reinterpretado como um estado motivacional caracterizado por um processo de intensa discriminação sensorial e por duas tendências simultâneas: uma de busca do familiar e outra de fuga do infamiliar

O problema mente-corpo: algumas consideraçöes sobre seu lugar na psicologia juntamente com uma proposta de reinterpretaçäo / The mind-body problem: some considerations about its place in psychology together with a proposal of reinterpretation

Apresenta-se o trabalho em 3 parte: na primeira, mostra-se como as idéias de Descartes - entre elas, a distinçäo mente-corpo - determinaram condiçöes para uma psicologia científica, mas envolvendo-a, também, em contradiçöes sobre seu objeto; na segunda, retoma-se a distinçäo para mostrar como, näo se nos impondo de maneira logicamente imperativa, nos deixa livres para ensaiar uma interpretaçäo alternativa; na última, propöe-se substituir a distinçäo mente-corpo por um sistema de relaçöes solidárias entre o organismo psicológico e o ambiente que permite entender as coisas fenomenais como compostas de aspectos presentes e aspectos de ajustamento dessas relaçöes, e extrai-se algumas implicaçöes psicológicas e filosóficas dessa proposiçäo

Mastoplastia pela técnica de Arié e suas variaçöes táticas / Mammaplasty by Arié technique and its tactical variations

É apresentada uma análise de dez anos de utilizaçäo do procedimento descrito por Arié, para a correçäo das ptoses e pequenas hipertrofias mamárias. Relata-se ainda o emprego de variaçöes táticas da técnica em questäo e os resultados obtidos

Trilha de formiga, senda de psicólogo e etólogo (meus caminhos e descaminhos no estudo do comportamento) / Ant's trail, the path of a psychologist and ethologist

Relata o caminho seguido na investigaçäo de certos comportamentos de aparência emocional em formigas, e a evoluçäo das interpretaçöes sobre esses fenômenos: reformula a interpretaçäo inicial, cognitivista, primeiramente em termos de condicionamento operante, o que se revelou improdutivo. Expöe a descoberta de outras possibilidades de interpretaçäo e propöe o conceito de um novo mecanismo de comportamento, adicional ao reflexo e ao padräo fixo de açäo, e täo automaticamente desencadeado e filogeneticamente determinado quanto aqueles. Esta demonstraçäo impöe uma reforma das concepçöes correntes a respeito da psicologia, da etologia e de suas relaçöes, além de prover esta última disciplina com condiçöes para tornar-se uma ciência completa do comportamento