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Affective flexibility is defined as a complex executive function which enables individuals to successfully alternate between distinct emotional and non-emotional features of a given situation in order to attain a specific goal. A large body of research has focused exclusively on flexibility in a non-emotional context, although most of our interactions with our environment are emotionally satiated. Our main aim was to propose a hierarchical framework to describe this construct from a macro-level perspective to a more nuanced and micro-level perspective, including three different levels of affective flexibility: elementary, shifting, and generative. Next, we employed this hierarchical framework to examine the role played by affective flexibility in typical development and different forms of developmental psychopathology. Lastly, we discuss how this knowledge could inform future prevention and intervention programs aimed at reducing cognitive vulnerability to developmental psychopathology., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Ischemic heart condition is one of the most prevalent causes of death that can be treated more effectively and lead to fewer fatalities if identified early. Heart muscle fibrosis affects the diastolic and systolic function of the heart and is linked to unfavorable cardiovascular outcomes. Cardiac magnetic resonance (CMR) scarring, a risk factor for ischemic heart disease, may be accurately identified by magnetic resonance imaging (MRI) to recognize fibrosis. In the past few decades, numerous methods based on MRI have been employed to identify and categorize cardiac fibrosis. Because they increase the therapeutic advantages and the likelihood that patients will survive, developing these approaches is essential and has significant medical benefits. A brand-new method that uses MRI has been suggested to help with diagnosing. Advances in deep learning (DL) networks contribute to the early and accurate diagnosis of heart muscle fibrosis. This study introduces a new deep network known as FibrosisNet, which detects and classifies fibrosis if it is present. It includes some of 17 various series layers to achieve the fibrosis detection target. The introduced classification system is trained and evaluated for the best performance results. In addition, deep transfer-learning models are applied to the different famous convolution neural networks to find fibrosis detection architectures. The FibrosisNet architecture achieves an accuracy of 96.05%, a sensitivity of 97.56%, and an F1-Score of 96.54%. The experimental results show that FibrosisNet has numerous benefits and produces higher results than current state-of-the-art methods and other advanced CNN approaches.

Background: The interplay between vitamin K (vitK) (as carboxylation cofactor, partially produced by the gut microbiota) and short-chain fatty acids (SCFAs), the end-product of fiber fermentation in the gut, has never been assessed in mother-newborn pairs, although newborns are considered vitK deficient and with sterile gut., Methods: We collected venous blood from 45 healthy mothers with uncomplicated term pregnancies and umbilical cord blood from their newborns at birth. The concentrations of total SCFAs and hepatic/extra-hepatic vitK-dependent proteins (VKDPs), as proxies of vitK status were assayed: undercarboxylated and total matrix Gla protein (ucMGP and tMGP), undercarboxylated osteocalcin (ucOC), undercarboxylated Gla-rich protein (ucGRP), and protein induced by vitK absence II (PIVKA-II)., Results: We found significantly higher ucOC (18.6-fold), ucMGP (9.2-fold), and PIVKA-II (5.6-fold) levels in newborns, while tMGP (5.1-fold) and SCFAs (2.4-fold) were higher in mothers, and ucGRP was insignificantly modified. In mother-newborn pairs, only ucGRP (r = 0.746, p < 0.01) and SCFAs (r = 0.428, p = 0.01) levels were correlated. Conclusions: We report for the first time the presence of SCFAs in humans at birth, probably transferred through the placenta to the fetus. The increased circulating undercarboxylated VKDPSs in newborns revealed a higher vitamin K deficiency at the extrahepatic level compared to liver VKDPs.

Background: The COVID-19 pandemic has caused morbidity and mortality, particularly among vulnerable populations. We aimed to assess social and demographic characteristics associated with COVID-19 severity among symptomatic participants during pregnancy., Methods: The International Registry of Coronavirus Exposure in Pregnancy is a multinational, longitudinal observational cohort study of adult participants tested for SARS-CoV-2 or who received clinical diagnosis of COVID-19 during pregnancy (NCT04366986). Disease severity status of mild, moderate, or severe was determined based on symptoms and healthcare utilization. Stratified by current versus recent pregnancy at enrollment, univariate mixed-effects logistic regression modeling was used to characterize association between social and demographic characteristics with COVID-19 severity, using a cumulative mixed effect model with country as a random effect., Results: The odds of developing more severe COVID-19 (odds ratio [95% confidence interval]) were higher among participants with lower socioeconomic status (poor: 2.72 [2.01,3.69]; lower-middle class: 2.07 [1.62,2.65] vs wealthy), among participants with lower educational attainment (high school: 1.68 [1.39,2.03]; < high school (1.77 [1.25,2.51] vs graduate education). Participants over 25 years of age had lower odds of severe COVID-19 versus participants < 25 years (25-34: 0.69 [0.56,0.85]; 35-50: 0.62 [0.48,0.80]). Employment in food services was also associated with increased odds of more severe COVID-19, whereas employment in healthcare and within home, and primiparity were associated with lower severity., Conclusions: Findings suggest that employment setting and economic status have strong associations with COVID-19 severity, which warrants considering social determinants of health in the context of assessing risk factors of more severe COVID-19 during pregnancy., Trial Registration: IRCEP was registered with the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (ENCePP) [EUPAS37360] and clinicaltrials.gov [NCT04366986]., (© 2022. The Author(s).)

Objective: We conducted literature reviews to uncover differential effects of sex on sequelae from coronavirus disease 2019 (COVID-19) and on long COVID syndrome., Methods: Two authors independently searched OvidSP in Embase, Medline, Biosis, and Derwent Drug File. Publications reporting original, sex-disaggregated data for sequelae of COVID-19 (published before August 2020) and long COVID syndrome (published before June 2021) were included in the reviews. The association between COVID-19 sequelae (i.e. lasting <4 weeks after symptom onset) and sex, and between long COVID syndrome (i.e. lasting >4 weeks after symptom onset) and sex, was determined by odds ratio (OR) and 95% confidence interval (CI) (statistical significance defined by 95% CI not including 1)., Results: Of 4346 publications identified, 23 and 12 met eligibility criteria for COVID-19 sequelae and long COVID syndrome, respectively. COVID-19 sequelae in the categories of psychiatric/mood (OR = 1.80; 95% CI: 1.35-2.41), ENT (OR = 1.42; 95% CI: 1.39-1.46), musculoskeletal (OR = 1.15; 95% CI: 1.14-1.16), and respiratory (OR = 1.09; 95% CI: 1.08-1.11) were significantly more likely among females (vs. males), whereas renal sequelae (OR = 0.83; 95% CI: 0.75-0.93) were significantly more likely among males. The likelihood of having long COVID syndrome was significantly greater among females (OR = 1.22; 95% CI: 1.13-1.32), with the odds of ENT (OR = 2.28; 95% CI: 1.94-2.67), GI (OR = 1.60; 95% CI: 1.04-2.44), psychiatric/mood (OR = 1.58; 95% CI: 1.37-1.82), neurological (OR = 1.30; 95% CI: 1.03-1.63), dermatological (OR = 1.29; 95% CI: 1.05-1.58), and other (OR = 1.36; 95% CI: 1.25-1.49) disorders significantly higher among females and the odds of endocrine (OR = 0.75; 95% CI: 0.69-0.81) and renal disorders (OR = 0.74; 95% CI: 0.64-0.86) significantly higher among males., Conclusions: Sex-disaggregated differences for COVID-19 sequelae and long COVID syndrome were observed. Few COVID-19 studies report sex-disaggregated data, underscoring the need for further sex-based research/reporting of COVID-19 disease.

The risk associated with extreme hydrological processes (flash floods, floods) is more present than ever, taking into account the global climatic changes, the expansion of inhabited areas and the changes emerging as a result of inadequate land management. Of all the hydrological risks, slope flash floods represent the processes that have the highest impact because of the high speed of their development and their place of origin, which makes them difficult to predict. This study is performed in an area susceptible to the emergence of slope flash floods, the Valea Rea catchment area, spatially located in Northwest Romania, and exposed to western circulation, which favours the development of such processes. The entire research is based on a methodology involving the integration of spatial databases, which indicate the vulnerability of the territory in the form of a weighted average equation to highlight the major impact of the most relevant factor. A number of 15 factors have been used in raster spatial databases, obtained by conversion (land use, soil type, lithology, Hydrologic Soil Group, etc.), derived from the digital elevation model (slope, aspect, TWI, etc.) or by performing spatial analysis submodels (precipitation, slope length, etc). The integration of these databases by means of the spatial analysis equation based on the weighted average led to the vulnerability of the territory to FFPI, classified on five classes from very low to very high. The final result underlines the high and very high vulnerability (43%) of the analysed territory that may have a major impact on the human communities and the territorial infrastructure. The results obtained highlight the torrential nature of the analysed catchment area, identifying several hotspots of great risk, located mainly within the built-up areas of intensely inhabited regions; a fact which involves a major risk and significant potential material damage in the territory. The model was validated by directly comparing the results obtained with locations previously affected, where the flood effects have been identified, highlighting the fact that the model may be taken into account to be applied in practice, and also to be implemented in territories that share the same features.