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The actual panorama of angiogenesis subtypes regarding breast cancers: an extensive examination using the Most cancers Genome Atlas.
Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. IKE modulator in vitro However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.Background Although the usual primary clinical manifestation of Coronavirus disease (COVID-19) is respiratory, several non-respiratory symptoms have been described, including neuropsychiatric ones. The aim of this study was to investigate the mid-term mental health outcomes in patients recovered from COVID-19, 3-4 months after discharge from the University Hospital Maggiore della Carità, Novara, Italy. Furthermore, we investigated the possible association of the mid-term mental health consequences of the COVID-19 infection with patients' clinical current status, persistent physical impairment and severity of acute phase of the disease. Methods Prospective study involving 238 individuals recovered from COVID-19. In the context of a multi-disciplinary approach, patients' assessment included both a clinical interview performed by an experienced psychiatrist, trained in the use of the Mini-International Neuropsychiatric Interview to assess the presence of anxiety and depressive symptoms and self-administered quesoach including both a psychiatric interview and the use of self-administered questionnaires is likely to capture the psychiatric outcome of patients recovered from COVID-19 better than questionnaires alone. Anxiety and depressive symptoms at follow-up had no correlation with the severity of COVID acute manifestations, but rather with ongoing and persistent physical symptoms. Further studies and longer follow-up duration will allow a better understanding of the complex relationship between residual physical symptoms, quality of life and psychological health.Introduction The notion that depression is a disorder that moves along a continuum is well-established. Similarly, the belief in the continuity of mental illness is considered an important element in the stigma process. Against this background, it is the aim of this study to examine whether public continuum beliefs vary with the severity of depressive symptoms. Methods Analyses were based on computer-assisted telephone interviews (CATIs) conducted in winter 2019/2020 in Germany (N = 1,009, response rate 46.8%). Using three vignettes representing mild, moderate, and severe depressive symptoms, beliefs regarding the continuity of symptoms, specifically a fundamental difference, were assessed with seven items. Sociodemographic characteristics and own experiences with depression (affliction and contact) were introduced as covariates. Results Significant differences between the three groups of severity were found for the majority of the items measuring continuum beliefs or perceived fundamental difference. However, only few items showed a linear trend indicating a parallel between symptom severity and beliefs. Multivariate regression models showed that a moderate degree of depression was positively associated with stronger continuum beliefs but also with greater perceived difference compared to the mild degree, while no significant associations emerged for the severe vignette. Limitations Although a comparison of our sample with official statistics supports the external validity, we cannot rule out a selection bias. It is arguable in how far short case vignettes convey a holistic picture of a person affected by depressive symptoms. Conclusion Our results do not indicate a parallel between symptom severity and public continuum beliefs.The aim of this study was to explore the mediating role of fatigue between mental health and its associated factors, including workload, social support, and occupational protection, among healthcare workers during the COVID-19 pandemic in China. A national cross-sectional survey was performed to collect data from healthcare workers who have attended to patients with COVID-19. Structural equation modeling (SEM) was conducted to test the mediating effect of fatigue. The results indicated that fatigue was a significant mediator of mental health. The proportion of indirect effect with regards to the total effect of workload on mental health was 54.2%, significantly greater than other factors such as social support (19.7%) and occupational protection (23.4%). The findings confirmed that workload, social support, and occupational protection both had indirect and direct effects on mental health status through fatigue. To some extent, potential interventions designed to alleviate fatigue would reduce mental health problems among healthcare workers during the COVID-19 pandemic.Background Erotomania, also known as de Clerambault's syndrome, is characterized by the delusion that a person has fallen in love with the patient. It occasionally appears secondary to psychiatric disorders and organic brain diseases. However, there have been no reports on cases secondary to dementia with Lewy bodies (DLB). Case Presentation The patient was an 83-year-old woman who lived alone. Mild cognitive impairment appeared at the age of 82 years. Soon after, she had the delusional conviction that her family doctor was in love with her. Her symptoms, such as gradually progressive cognitive impairment, cognitive fluctuations, and parkinsonism, indicated DLB. She was treated with a small dose of antipsychotic agents. Conclusions This case report suggests the possibility of de Clerambault's syndrome during the early stages of DLB. Further investigations are required to clarify the mechanism and treatment of de Clerambault's syndrome in patients with DLB.
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