Assessing atypical brain functional connectivity development: An approach based on generative adversarial networks.

Generative Adversarial Networks (GANs) are promising analytical tools in machine learning applications. Characterizing atypical neurodevelopmental processes might be useful in establishing diagnostic and prognostic biomarkers of psychiatric disorders. In this article, we investigate the potential of GANs models combined with functional connectivity (FC) measures to build a predictive neurotypicality score 3-years after scanning. We used a ROI-to-ROI analysis of resting-state functional magnetic resonance imaging (fMRI) data from a community-based cohort of children and adolescents (377 neurotypical and 126 atypical participants). Models were trained on data from neurotypical participants, capturing their sample variability of FC. The discriminator subnetwork of each GAN model discriminated between the learned neurotypical functional connectivity pattern and atypical or unrelated patterns. Discriminator models were combined in ensembles, improving discrimination performance. Explanations for the model's predictions are provided using the LIME (Local Interpretable Model-Agnostic) algorithm and local hubs are identified in light of these explanations. Our findings suggest this approach is a promising strategy to build potential biomarkers based on functional connectivity.

CAAos platform: an integrated platform for analysis of cerebral hemodynamics data.

Objective.The purpose of this article is to introduce readers to the concept and structure of the CAAos (CerebralAutoregulationAssessmentOpenSource) platform, and provide evidence of its functionality.Approach.The CAAos platform is a new open-source software research tool, developed in Python 3 language, that combines existing and novel methods for interactive visual inspection, batch processing and analysis of multichannel records. The platform is scalable, allowing for the customization and inclusion of new tools.Main results.Currently, the CAAos platform is composed of two main modules, preprocessing (containing artefact removal, filtering and signal beat to beat extraction tools) and cerebral autoregulation (CA) analysis modules. Two methods for assessing CA have been implemented into the CAAos platform: transfer function analysis (TFA) and the autoregulation index (ARI). In order to provide validation of the TFA and ARI estimates derived from the CAAos platform, the results were compared with those derived from two other algorithms. Validation was performed using data from 28 participants, corresponding to 13 acute ischemic stroke patients and 13 age- and sex-matched control subjects. Agreement between estimates was assessed by intraclass correlation coefficient and Bland-Altman analysis. No significant statistical difference between the algorithms was found. Moreover, there was an excellent correspondence between the curves of all parameters analysed, with the intraclass correlation coefficient ranging from 0.98 (95%CI 0.976-0.999) to 1.00 (95%CI 1 -1). The mean differences revealed a very small magnitude bias indicating an excellent agreement between the estimates.Significance.As open-source software, the source code for the software is freely available for noncommercial use, reducing barriers to performing CA analysis, allowing inspection of the inner-workings of the algorithms, and facilitating networked activities with common standards. The CAAos platform is a tailored software solution for the scientific community in the cerebral hemodynamic field and contributes to the increasing use and reproducibility of CA assessment.

Burnout in the Pharmaceutical Activity: The Impact of COVID-19.

IMPORTANCE: Pharmacists are among the healthcare professionals involved in the response to the COVID-19 pandemic, maintaining essential services. In the context of restrictions and reorganization of human resources, as a result of policies recently applied to the health sector, following international guidelines, and given the scarcity of data on burnout in pharmaceutical activity, it was considered highly relevant to promote a nationwide survey aiming to collect more complete evidence on the burnout syndrome and to understand how pharmacists have viewed their work and the people they worked closely with. OBJECTIVES: The study aimed to assess the occurrence of pharmacist burnout and determine outcomes for each of its dimensions; identify potentially associated characteristics; and determine profiles and critical limits. DESIGN: A cross-sectional observational study conducted by a multidisciplinary panel from the Portuguese Pharmaceutical Society (PPS). Professionals from community and hospital pharmacies who were at the forefront of the COVID-19 response were involved in (i) confirming the need and pertinence for conducting this research, (ii) identifying the main factors leading to pharmaceutical emotional distress ("burnout"), and (iii) disseminating the survey. The questionnaire was designed for digital voluntary, confidential, and anonymous participation and divided into four segments of data collection: (i) demographics, (ii) employment and workplace characterization, (iii) pandemic impact on labor activity, and (iv) burnout assessment (as described ahead). SETTING: An electronic survey was addressed to all PPS members, and an account was created solely to manage the questionnaire data for the research team. The web-based and user-friendly platform Google Forms supported the data capture and provided an intuitive interface for validated data entry. PARTICIPANTS: In a population of 15,565 pharmacists (members of the PPS), the minimum recommended sample size (Epi Info software), with a 5% margin of error and a 99.9% confidence interval, should be 1,012 individuals. A total of 1,362 pharmacists participated in the study. Of these, 91.4% (n = 1,246) were involved in direct patient care activity and 7.7% (n = 106) in non-direct patient care activity.

Screening of Dementia in Portuguese Primary Care: Methodology, Assessment Tools, and Main Results.

The objectives of this article are as follows: (1) to describe the assessment protocol used to outline people with probable dementia in Primary Health Care; (2) to show the methodological design and procedure to obtain a representative sample of patients with probable dementia; and (3) to report the main characteristics of the sample collected in the context of the study "Characteristics and needs of people with probable dementia." The study protocol was based on the "Community Assessment of Risk and Treatment Strategies (CARTS) Program" and is composed by a set of instruments that allow the assessment of older adults with probable dementia in several areas (health, psychological, functionality, and other). Descriptive analysis was used to characterize the final sample (n = 436). The study protocol as well as the methodological procedure to obtain the referral of research participants and data collection on the condition of people with probable dementia in Primary Health Care proved to be a valuable tool to obtain a sample of patients distributed by the full range of probable dementia in a large geographical area. Results may allocate the design of care pathways for old people with cognitive disorders to prevent, delay impairment, and/or optimize quality of life of patients.